Production ML Engineer Jobs in Bengaluru

Lead Machine Learning Engineer - NLP Location: Bengaluru About Us: Observe.AI Observe.AI is the leading AI agent platform for customer experience. It enables enterprises to deploy AI agents that automate customer interactions, delivering natural conversations for customers with predictable outcomes for the business. Observe.AI combines advanced speech understanding, workflow automation, and enterprise-grade governance to execute end-to-end workflows with AI agents. It also enables teams to guide and augment human agents with AI copilots, and analyze 100% of human and AI interactions for insights, coaching, and quality management. Companies like DoorDash, Affordable Care, Signify Health, and Verida use Observe.AI to transform customer experiences every day by accelerating service speed, increasing operational efficiency, and strengthening customer loyalty across every channel. You will be shaping how AI transforms real-world challenges in the contact center space. As part of our world-class ML team, you ll work on developing cutting-edge LLM-powered solutions & Agentic AI, building end-to-end processing pipelines, and handling production challenges at scale millions of interactions daily. If you are truly an engineer at heart, excited about turning breakthroughs in multi-agent systems, LLMs, NLP, and ML into practical outcomes through applied research, and building scalable production systems, you will feel right at home. You ll also have the opportunity to publish in top conferences, and influence Observe.AI s product and platform strategy. What you ll be doing Design & develop state-of-the-art LLM-powered AI capabilities and Agentic AI/ Multi-agent systems end-to-end, from ideation to production for Observe.AI s product offerings, in a fast-paced startup environment. Work with cutting-edge tools and technologies in Machine Learning, Deep Learning & Natural Language Processing, including LLMs and LLM-powered technologies/ paradigms, including Agentic AI. Build/ maintain highly scalable production systems that power AI capabilities on Observe.AI product/ platform. Optimize ML models and processing pipelines for performance, cost-effectiveness, and scale. Work with a world-class ML team in building exciting stuff, mentor juniors, and influence peers/ stakeholders. Collaborate cross-team with engineers, product managers, customer-facing teams, and customers to understand pain points and business opportunities. Keep up-to-date with the latest ML/ DL/ NLP literature and influence the technological evolution of Observe.AI platform. Contribute to the community through tech blogs and publishing papers in ML/ NLP conferences like EMNLP, ACL, etc. What you ll bring to the role Education: Bachelor s or Master s degree in Computer Science or related disciplines from a top-tier institution with exposure to ML/ DL/ NLP/ NLU. An engineering mindset with the competencies of an applied scientist. 5+ years of industry experience in building large-scale NLP/ NLU systems, with recent experience in building LLM-powered applications and Agentic systems. Strong understanding of the fundamentals of ML and NLP/ NLU, and practical aspects of building ML systems in production. Good understanding of recent advances in building LLM-powered applications, and multi-agent systems at scale. Excellent implementation skills in Python and Machine Learning Frameworks such as Pytorch, Tensorflow, HuggingFace, etc., and deploying/ maintaining scalable machine learning systems in production. Ability to provide thought leadership in one or more technical areas of interest to Observe.AI, and influence product development. Excellent communication, collaboration skills, and presentation skills. Experience with Spoken Language Understanding is a plus. Published papers in top NLP/ NLU conferences or workshops are a plus. Relevant open-source contributions are a plus. Perks & Benefits Medical Insurance: Excellent options and free online doctor consultations. Leave Policies: Yearly privilege and sick leaves as per Karnataka S&E Act, generous holidays (National and Festive) recognition and parental leave policies. Learning & Development fund to support your continuous learning journey and professional development. Fun events to build culture across the organization. Flexible benefit plans for tax exemptions (i.e. Meal card, PF, etc.). Qualification : Bachelors or Masters degree in Computer Science or related disciplines from a top-tier institution with exposure to ML/ DL/ NLP/ NLU

Analytics Engineer Location: Bengaluru Work Type: Full-Time About Postman Postman is the world s leading API platform, used by over 40 million developers and 500,000 organizations, including 98% of the Fortune 500. Our mission is to build an API-first world, simplifying every step of the API lifecycle and enabling teams to create better APIs, faster. Founded in Bengaluru, Postman is headquartered in San Francisco, with offices in Boston, New York, and Bengaluru. We are privately held, backed by Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. The Opportunity We are seeking an Analytics Engineer to join our Data Team and help strengthen the foundation of our modern data stack. In this role, you will own critical transformation pipelines, design scalable data models, and ensure that our analytics environment is performant, reliable, and future-ready. You will operate with a high degree of independence, driving projects from design through production, while implementing best practices in dbt, semantic layers, medallion architecture, and lakehouse paradigms. Key Responsibilities Take ownership of large portions of our dbt project (3k+ models), ensuring scalability, maintainability, and adherence to best practices. Design and implement robust data models, including dimensional modeling, incremental strategies, and Slowly Changing Dimensions (SCDs). Establish and enforce dbt test coverage, automated quality checks, and CI/CD pipeline standards using GitHub Actions. Profile and optimize SQL queries and warehouse performance for efficiency and cost reduction. Build and refine our semantic layer, ensuring consistent business logic across Looker, Redash, and downstream tools. Collaborate with analysts and business partners to define metrics and deliver self-serve data assets. Document models, lineage, and transformation logic to make data discoverable and usable across the company. Contribute to shaping team standards and playbooks, collaborating with analysts on modeling and transformation best practices. Stay ahead of modern data stack innovations, including dbt metrics layer, universal semantic layers, data contracts, and observability. Enabling Self-Serve Analytics & AI Build transformations that empower business stakeholders and analysts to explore data confidently. Ensure metric definitions are consistent, discoverable, and reusable across BI tools. Prepare clean, structured, and accessible datasets for AI-driven initiatives like conversational analytics and anomaly detection. Partner with Data Science & ML teams to provide reliable pipelines that accelerate experimentation and AI/ML deployment. About You 3 5 years of experience in analytics engineering roles. Advanced SQL skills (query optimization, performance tuning). Strong proficiency in dbt Core: models, macros, snapshots, sources, and custom materializations. Solid background in data modeling techniques (Kimball, SCD handling, incremental pipelines). Practical experience with semantic layers and BI integration (LookML, dbt metrics, or equivalent). Familiarity with Medallion architecture and modern lakehouse approaches. Hands-on experience with Redshift; exposure to Databricks is a plus. Proficiency with GitHub and CI/CD pipelines for analytics code. Strong fundamentals in data quality, governance, and lineage tracking. Flexible schedule with a hybrid work model. Full medical coverage, flexible PTO, wellness reimbursement, and monthly lunch stipend. Access to wellness programs, team-building events, and donation-matching initiatives. An inclusive, collaborative culture where everyone can thrive and grow. Our Values Curiosity: Explore and innovate fearlessly. Transparency: Communicate openly about successes and failures. Focus: Set clear goals aligned with a bold vision. Inclusion: Every voice matters. Excellence: Deliver the best products and experiences together.

Data Scientist I Job Type: Full-Time Category: Data Science Location: Bangalore About Bright Money Bright is a mission-driven consumer fintech company helping Americans get out of debt and build stronger financial futures powered by data science and machine learning. Our mobile platform provides personalized tools for credit building, debt paydown, budgeting, and loan refinancing. With 300,000+ users, 100,000+ reviews, and support from top-tier investors like Sequoia, Falcon Edge, and Hummingbird, Bright is one of the fastest-growing fintech startups in the U.S. We ve raised $90M+ in equity and debt funding to date. We're proud to be building a global-first, data-driven consumer tech company from India, for the world. About the Role As a Data Scientist I, you will be part of a high-impact team using data and machine learning to power Bright s core financial products. You ll work on problems that directly improve users financial outcomes modeling behavior, predicting intent, and enabling smarter, automated experiences. This is a hands-on role for someone with strong fundamentals in ML, statistics, and programming, and a desire to turn data into real-world product impact. Key Responsibilities Design and build predictive models using core concepts of machine learning, statistics, and probability. Analyze large-scale user and transactional data to extract insights and inform strategy. Collaborate cross-functionally with product managers, engineers, and business stakeholders to define and solve problems. Deploy ML models into production environments, ensuring scalability, stability, and performance. Tune, evaluate, and interpret model results to maximize business value and user outcomes. Document methodologies and workflows for reproducibility and team collaboration. Stay current with AI/ML advancements and experiment with new techniques as appropriate. Required Qualifications Bachelor s or Master s degree in Computer Science, Statistics, Mathematics, or a related quantitative field. Strong grasp of ML and statistical concepts (e.g., regression, classification, hypothesis testing, probability distributions). Proficiency in Python or R, and experience with ML libraries such as scikit-learn, TensorFlow, or PyTorch. Familiarity with model deployment tools and frameworks (e.g., Docker, Flask/FastAPI, MLflow). Understanding of how to implement and monitor models in a real-world production environment. Awareness of modern AI techniques including transformers, LLMs, and generative AI. Strong problem-solving skills, curiosity, and ability to communicate complex ideas clearly. Exposure to cloud platforms like AWS, GCP, or Azure is a plus. Bonus Points For Experience with deep learning and advanced neural network architectures. Understanding of MLOps best practices (CI/CD for ML, monitoring, retraining pipelines). Personal projects, open-source contributions, or research publications in AI/ML. What You ll Work On Model user behavior and financial patterns to power intelligent product features. Analyze complex transaction datasets to surface actionable insights. Build and deploy ML systems that personalize savings and debt management strategies. Apply deep learning, reinforcement learning, and LLMs to real-world fintech use cases. Collaborate with engineering and product teams to launch data-powered experiences in the Bright app. Experiment with cutting-edge AI technologies to innovate in consumer finance. At Bright, you ll go beyond theory you ll use data to change lives. This is your chance to build meaningful, scalable machine learning systems that empower users to take control of their financial future. Qualification : Bachelors or Masters degree in Computer Science, Statistics, Mathematics, or a related quantitative field

Job Title: AI/ML Engineer Location: Bangalore Experience: 4 5 Years Qualification: Bachelor s or Master s Degree in Computer Science or a related field Job Description Design and develop machine learning and deep learning systems tailored to business needs. Select and preprocess appropriate datasets; implement and optimize ML algorithms. Conduct machine learning experiments, run tests, and perform statistical analysis to fine-tune models. Train, retrain, and maintain ML systems to ensure accuracy and performance. Extend and customize existing ML libraries and frameworks. Stay updated with the latest research and advancements in machine learning and AI. Requirements Proven experience as a Machine Learning Engineer or similar role. Strong understanding of data structures, data modeling, and software architecture. Deep knowledge of mathematics, probability, statistics, and algorithms relevant to ML. Proficiency in writing clean, robust code in Python. Experience with ML frameworks such as TensorFlow or PyTorch, and libraries like scikit-learn. Skilled in deploying ML models and developing APIs for production environments. Experience with AWS cloud and ML services; knowledge of SageMaker is a plus. Qualification : Bachelors or Masters Degree in Computer Science or a related field

Distinguished Engineer Machine Learning Engineering Location: Bangalore Company: Capital One India About Us At Capital One India, we re redefining how technology powers financial services. Our teams work in a fast-paced, intellectually rigorous environment to tackle complex business challenges at scale. By harnessing the power of advanced analytics, data science, and machine learning, we create innovative, patentable solutions that transform customer experiences and drive the business forward. Team Overview: Machine Learning Experience (MLX) The MLX team leads Capital One s mission to build scalable, well-managed ML systems and platforms. We empower teams across the enterprise to develop, govern, and deploy machine learning models efficiently, securely, and at scale. From automated model governance to observability platforms, MLX enables end-to-end ML lifecycle management laying the foundation for AI-driven innovation across the organization. Role Overview We re looking for a Distinguished Engineer Machine Learning Engineering to join our MLX team. In this high-impact role, you'll architect and implement the platforms and tools that support model observability, automated governance, and ML model deployment at scale. This is an opportunity to drive enterprise-wide innovation and shape how ML is integrated into Capital One s core business systems. What You ll Do Design and build systems that capture and analyze large-scale model and feature metadata, including training metrics and runtime performance, to power model observability and governance automation. Partner with cross-functional teams including product managers, designers, and platform engineers to create scalable solutions that accelerate ML model lifecycle management. Lead efforts to enable automated governance decisions for ML models, ensuring compliance, auditability, and operational integrity. Architect and implement high-performance data pipelines that feed ML models with real-time and batch data. Contribute to the design and implementation of cloud-native ML systems using tools such as AWS, Kubernetes, and Terraform. Write clean, scalable, production-grade code in languages like Python, Go, or Java. Implement CI/CD pipelines, testing frameworks, and monitoring systems for ML applications. Drive the adoption of best practices in ML Ops, observability, and platform resilience. Basic Qualifications Master s Degree in Computer Science or related field. 15+ years of experience in software engineering or solution architecture. 10+ years building data-intensive, distributed computing systems. 10+ years programming in Python, Go, or Java. 8+ years of hands-on experience with industry-leading ML frameworks (e.g., Scikit-learn, TensorFlow, PyTorch, Dask, Spark). Preferred Qualifications PhD or Master's in Computer Science, Electrical Engineering, Mathematics, or related field. 5+ years of experience building, scaling, and optimizing production ML systems. Deep expertise in data preparation, feature engineering, and ML pipeline optimization. 10+ years writing performant, maintainable, and resilient production code. Strong experience deploying ML solutions on public cloud platforms (AWS, Azure, GCP). Expertise in distributed systems, file systems, or multi-node databases. Open-source contributor to ML tools or libraries. Published work in ML (papers, patents, blogs, etc.). 5+ years of experience in ML Ops (using MLflow, TFX, Kubeflow, etc.). Experience with LLMs and Generative AI applications (open-source or commercial models). Proven experience designing production-ready observability platforms for ML applications. Be at the forefront of building scalable, secure, and enterprise-grade ML platforms. Shape the future of AI and ML adoption in a top-tier financial institution. Collaborate with world-class engineers and data scientists. Solve real-world problems with high business impact. Thrive in a diverse, inclusive, and innovation-focused culture. Qualification : PhD or Master's in Computer Science, Electrical Engineering, Mathematics, or related field

Lead Fullstack Engineer Location: Bangalore Company: Capital One India About Capital One India At Capital One India, we thrive in a fast-paced, intellectually rigorous environment where we solve real-world business problems at scale. By combining advanced analytics, data science, and machine learning, we unlock powerful insights and build cutting-edge, patentable technology products that drive innovation and impact. Team Overview: Machine Learning Experiences (MLX) The MLX team is at the core of Capital One s AI/ML transformation. We re shaping the way the enterprise builds, deploys, and monitors ML models and features providing the tools and platforms that enable every business line to deliver AI-powered experiences. From platform onboarding to observability, MLX sets the foundation for responsible, scalable machine learning across Capital One. Role Overview We are seeking a Lead Fullstack Engineer to architect and develop scalable, cloud-native applications that power our ML platforms. You ll be responsible for leading technical initiatives, mentoring team members, and driving the development of full-stack systems with a primary focus on Python and Go, and a working proficiency in React. This is a hands-on leadership role requiring deep cloud expertise (AWS), backend scalability know-how, and familiarity with ML observability concepts. What You ll Do Lead cross-functional teams on full-stack development projects that support machine learning platforms and observability tools. Design and develop robust applications using Python, Go, and React, adhering to scalable and maintainable coding principles. Architect cloud-native solutions on AWS, leveraging services such as Lambda, ECS, S3, DynamoDB, SQS, and IAM. Implement and optimize CI/CD pipelines, containerization with Docker/Kubernetes, and other DevOps best practices. Work closely with ML engineers and data scientists to enhance observability and monitoring for ML models in production. Utilize open-source frameworks to accelerate development and maintain system performance. Collaborate with product managers to deliver user-centric, cloud-based solutions that drive real customer impact. Conduct code reviews, mentor engineers, and maintain high technical standards across the team. Contribute to backend optimization, API development, and integration with real-time data systems. Required Qualifications 7 10 years of experience in software development, with a strong background in backend and full-stack systems. Expertise in Python and Go; strong ability to build scalable, maintainable systems. Proficiency in React for frontend development (medium level). Hands-on experience with AWS services such as Lambda, ECS, S3, DynamoDB, IAM, and SQS. Experience with ML observability frameworks and tools. Knowledge of open-source development frameworks and cloud architecture patterns. Proficiency in CI/CD, containerization (Docker, Kubernetes), and modern DevOps practices. Strong problem-solving abilities and a track record of leading technical initiatives in agile environments. Preferred Qualifications Experience monitoring ML models in production and integrating observability tools. Knowledge of event-driven architecture and microservices. Familiarity with GraphQL, WebSockets, and real-time data communication. Understanding of data streaming architectures and processing pipelines. Why Join Capital One Be part of a team building enterprise-scale platforms that power ML for millions of customers. Work on impactful, cloud-native solutions in a collaborative and high-growth environment. Collaborate with world-class engineers, data scientists, and product leaders. Enjoy a culture that values experimentation, learning, and technical excellence.

Principal Associate Full Stack Engineering (GenAI Observability) Location: Bangalore Company: Capital One India About Us At Capital One India, we re tackling some of the most complex problems in financial services using machine learning, advanced analytics, and cloud-first engineering. Our mission is to build cutting-edge, patentable solutions that transform customer experiences, enhance operational efficiency, and ensure robust risk and compliance standards. We re a team of makers, breakers, doers, and disruptors obsessed with turning data into real-world impact at scale. About the Team Machine Learning Experiences (MLX) The MLX team is pioneering the future of model governance, ML observability, and Generative AI infrastructure at Capital One. We re enabling teams to seamlessly deploy ML and GenAI models at scale, with full visibility into performance, health, compliance, and ethical usage. This is the platform powering the next generation of AI-driven financial products across the company. About the Role We re looking for a Principal Associate Full Stack Engineer to lead the development of observability platforms for Generative AI systems. You ll be part of a cross-functional team focused on governance automation, LLM monitoring, and intelligent diagnostics using telemetry data, metadata, and advanced analytics. You ll design systems to collect, analyze, and visualize performance data from our large-scale GenAI infrastructure, helping data scientists and engineers make faster, safer decisions. What You ll Do Lead architecture and development of observability tools and dashboards for monitoring GenAI models and platform health. Design and build core APIs and SDKs to instrument large language models (LLMs) and foundational models (training, fine-tuning, prompting stages). Integrate Generative AI to enable observability features like anomaly detection, predictive analytics, and copilot-assisted troubleshooting. Partner with platform, MLOps, and governance teams to ingest and analyze telemetry, metadata, and runtime metrics at scale. Drive development of tools to ensure compliance with AI ethics, data governance, and industry regulations. Collaborate with product, design, and research to turn complex requirements into scalable, cloud-native software solutions. Lead proof-of-concept initiatives to test and showcase how GenAI can improve platform observability and decision-making. Contribute to the open-source community and stay at the forefront of GenAI and ML infrastructure evolution. Basic Qualifications Bachelor s or Master s degree in Computer Science, Engineering, or related field 4+ years of experience building distributed, data-intensive systems using microservices architecture 4+ years of experience in backend development with Python, Go, or Java 4+ years of expertise with observability stacks (Prometheus, Grafana, ELK) and adapting them for AI systems Strong knowledge of OpenTelemetry, and experience building custom SDKs and APIs 5+ years of hands-on experience with Generative AI models, especially applied to observability, governance, or compliance 2+ years of experience with cloud platforms such as AWS, Azure, or GCP Preferred Qualifications 4+ years building and optimizing ML systems in production environments 3+ years of experience with MLOps tools like MLflow, Kubeflow, or commercial platforms Experience with GenAI frameworks and libraries like LangChain, Haystack, and vector databases (FAISS, Chroma, OpenSearch) Familiarity with emerging observability tools for LLMs such as Langfuse, Phoenix, Helicone, or OpenInference Contributor to open-source GenAI or ML infrastructure projects Author or co-author of published work in AI/ML observability, governance, or performance monitoring Experience with PyTorch, TensorFlow, Spark, or Dask Knowledge of NVIDIA GPU telemetry, CUDA programming, and performance optimization for AI workloads Understanding of AI ethics, data governance, and regulatory frameworks for machine learning systems Why Join Capital One India Work at the intersection of technology, AI, and compliance helping shape the future of responsible AI Join a team driving enterprise-wide adoption of Generative AI Collaborate with world-class engineers, data scientists, and product leaders Enjoy a high-performance culture that encourages innovation, learning, and mentorship Access to cutting-edge tools, open-source contributions, and cloud-native infrastructure Qualification : Bachelors or Masters degree in Computer Science, Engineering, or related field

Job Title: Associate ML Ops Location: Bangalore Department: Data Science Employment Type: Full-time Experience: 1 2 years Job Overview We are seeking a motivated and detail-oriented Associate ML Ops to join our Data Science team. In this role, you will be responsible for supporting the deployment, monitoring, and scaling of machine learning models in production environments. You ll collaborate closely with data scientists and engineers to build robust MLOps pipelines and ensure model reliability, scalability, and performance. If you are passionate about bringing machine learning models to life and have hands-on experience in productionizing ML systems, we d love to hear from you. Key Responsibilities Deploy and maintain machine learning models in production environments using best-in-class tools like Databricks and MLflow. Collaborate with data scientists to translate experimental models into scalable, production-ready systems. Monitor model performance, accuracy, and overall health through automated tools and custom strategies. Build and maintain RESTful APIs using Python frameworks such as Flask or Django to serve ML models. Write efficient and optimized SQL and NoSQL queries for data extraction and transformation. Apply software engineering best practices, including version control, testing, and documentation, to MLOps workflows. Work with Python libraries like Pandas, PySpark, scikit-learn, SQLAlchemy, and Requests. Troubleshoot issues related to model deployment, API performance, or data integration pipelines. Minimum Qualifications Bachelor s or Master s degree in Computer Science, Statistics, Econometrics, Operations Research, or a related technical field. 1 2 years of hands-on experience in solving analytical or machine learning problems in production settings. Must-Have Technical Skills Hands-on experience with Databricks and MLflow Proven expertise in deploying ML models in real-world applications Strong understanding of data structures, algorithms, OOP, and software engineering principles Experience building and maintaining REST APIs using Python Proficiency in SQL and NoSQL Excellent Python programming and debugging skills Familiarity with core Python libraries used in ML and data processing: Pandas, scikit-learn, PySpark, SQLAlchemy, etc. Nice-to-Have Skills Exposure to Kafka for streaming and batch data processing Familiarity with Git and CI/CD pipelines Experience with Python multiprocessing or worker/queue systems Understanding of event-driven or asynchronous programming models This is an exciting opportunity to work at the intersection of data science and engineering. You ll play a key role in productionizing cutting-edge models and ensuring they deliver real business impact. Qualification : Bachelors or Masters degree in Computer Science, Statistics, Econometrics, Operations Research, or a related technical field

Job Title: ML Ops Engineer Location: Bangalore Department: Data Science Employee Type: Full-time Experience Required: 3 5 years Position Overview We are seeking an experienced and motivated ML Ops Engineer to join our Data Science team. In this role, you will be responsible for deploying, monitoring, and maintaining machine learning models in production environments. You will work closely with data scientists, engineers, and product teams to ensure models are scalable, reliable, and aligned with business objectives. This role is ideal for professionals who are passionate about building robust ML pipelines and bringing machine learning solutions into real-world applications at scale. Key Responsibilities Deploy and manage machine learning models in production environments, ensuring scalability, reliability, and performance. Build and maintain MLOps pipelines using platforms like Databricks and MLflow. Monitor model performance, accuracy, and health; implement alerting and diagnostics as needed. Develop and maintain RESTful APIs using Python frameworks such as Flask or Django to serve ML models. Optimize data workflows and collaborate with engineering teams to improve model integration and performance. Design strategies for automated model retraining, deployment, and version control. Write clean, maintainable, and efficient code using Python, adhering to OOP principles and best practices. Write complex queries using SQL and work with NoSQL databases to support data pipelines and feature stores. Leverage Python libraries such as PySpark, Pandas, scikit-learn, SQLAlchemy, and Requests. Minimum Qualifications Bachelor s or Master s degree in Computer Science, Statistics, Econometrics, Operations Research, or a related technical field. 3 5 years of experience in building, deploying, and monitoring machine learning solutions in production. Must-Have Skills Experience with Databricks and MLflow for model training and deployment. Proven expertise in machine learning model deployment and monitoring in live environments. Strong programming skills in Python, with solid understanding of data structures, algorithms, and OOP concepts. Experience developing RESTful APIs using Flask or Django. Proficient in SQL and NoSQL database operations. Hands-on knowledge of libraries such as Pandas, PySpark, scikit-learn, SQLAlchemy, and Requests. Strong analytical, problem-solving, and debugging skills. Good-to-Have Skills Experience with Kafka streaming and batch processing. Familiarity with CI/CD pipelines and version control systems like Git. Understanding of Python multiprocessing, worker/queue systems, and asynchronous/event-driven programming. This is a unique opportunity to work at the intersection of machine learning and DevOps. You'll play a critical role in operationalizing AI models and making them a core part of our product offerings. If you enjoy building scalable systems and solving real-world ML engineering challenges, we d love to meet you. Qualification : Bachelors or Masters degree in Computer Science, Statistics, Econometrics, Operations Research, or a related technical field

Position: Senior Data Scientist LLM Location: Bangalore, Karnataka, India Type: Full-Time (On-site) Experience Required: 2+ years in Deep Learning, 1+ years in LLMs Industry: Healthcare AI Company Overview: 5C Network is pioneering multi-modal AI systems for autonomous diagnosis in medical imaging. We're building next-generation models that integrate deep learning with language understanding to revolutionize clinical workflows and diagnostic accuracy. Role Summary: As a Senior Data Scientist LLM, you will lead the development and deployment of Large Language Models (LLMs) focused on enhancing medical imaging diagnostics. You ll work on cutting-edge problems such as instruction fine-tuning, prompt engineering, and Retrieval-Augmented Generation (RAG), while ensuring scalability and robustness in production environments. Key Responsibilities: LLM Development & Fine-Tuning Design and optimize prompts for diverse clinical and imaging-related use cases. Perform instruction fine-tuning of LLMs to meet task-specific requirements. Develop reasoning pipelines including Chain of Thought (CoT) techniques for complex diagnostic workflows. LLM Deployment & Optimization Self-host and deploy LLMs in secure, scalable production environments. Apply quantization and other performance optimization methods to minimize compute and memory footprint. Ensure high performance, uptime, and security in AI deployments. Retrieval-Augmented Generation (RAG) & Vector Databases Develop and implement RAG pipelines by integrating LLMs with semantic search. Work with vector databases (e.g., Qdrant) to enable fast, efficient retrieval of contextual data. Optimize data storage, indexing, and retrieval to support clinical applications. Data Engineering & Annotation Build and manage high-quality datasets tailored for CoT and multi-step reasoning tasks. Lead data annotation efforts to enhance LLM understanding of medical contexts. Collaboration & Research Collaborate with researchers, ML engineers, and domain experts to bring LLM solutions from prototype to product. Stay ahead of the curve by experimenting with novel LLM architectures and emerging techniques. Qualifications: Bachelor's or Master s degree in Computer Science, Data Science, AI, or a related field. 2+ years of hands-on experience in deep learning. Minimum 1 year of experience working with LLMs (e.g., instruction tuning, prompt engineering, RAG). Prior experience in LLM deployment (self-hosting, optimization, quantization, scaling). Proficient in Python and common ML frameworks (e.g., PyTorch, Hugging Face Transformers). Familiarity with vector databases like Qdrant or similar. Strong interest or prior exposure to healthcare/medical AI. Excellent problem-solving, communication, and team collaboration skills. Technical Stack: Languages: Python Frameworks: PyTorch, Hugging Face Technologies: LLMs (e.g., GPT, LLaMA), Vector Databases (Qdrant), RAG, Quantization Tools: Docker, Kubernetes, REST APIs, Git Work on high-impact AI solutions in the healthcare domain. Collaborate with a team at the forefront of multi-modal diagnostic technology. Access cutting-edge tools and real-world data to drive innovation. Qualification : Bachelor's or Masters degree in Computer Science, Data Science, AI, or a related field.

Position Title: Lead AI/ML Engineer Location: Bengaluru Bellandur (GTP) Employment Type: Full-time Job Summary Synechron is seeking a seasoned Lead AI/ML Engineer to lead cutting-edge initiatives in artificial intelligence and machine learning. This role requires deep technical expertise in AI/ML, including deep learning, NLP, computer vision, and generative AI, combined with strong leadership skills to manage teams and drive innovation. You will collaborate closely with stakeholders to deliver high-impact solutions and play a key role in shaping the company s AI-driven digital transformation. Key Responsibilities Lead end-to-end development of AI/ML solutions across use cases involving machine learning, deep learning, computer vision, NLP, and generative AI. Design and implement scalable models and algorithms, ensuring performance, accuracy, and interpretability. Collaborate with product owners, engineers, and business stakeholders to align AI/ML initiatives with strategic objectives. Mentor and guide data scientists and ML engineers to elevate technical quality and delivery standards. Continuously evaluate emerging AI technologies, frameworks, and methodologies to enhance team capabilities. Contribute to innovation strategy by identifying new business opportunities driven by AI/ML. Ensure data and model governance, ethical AI practices, and responsible deployment of AI solutions. Required Skills & Tools Core Competencies: Strong hands-on experience in machine learning, deep learning, NLP, computer vision, and generative AI. Expertise in Python (primary), with additional knowledge of R, SQL, Java, or C++. Deep understanding of statistics, linear algebra, probability, and algorithm design. Frameworks & Tools: TensorFlow, PyTorch, Keras, OpenCV, Hugging Face, spaCy, Scikit-learn, etc. Data processing tools like Pandas, NumPy, and Spark. Version control and CI/CD tools (e.g., Git, MLflow, Docker, Airflow). Methodologies: Proficient in Agile development and model lifecycle management. Experience with productionizing AI models and deploying them on cloud platforms (AWS, Azure, GCP). Experience 8 12 years of experience in AI/ML, Data Science, or related domains. Minimum 8+ years in a leadership or technical lead role driving successful AI/ML initiatives. Proven record of delivering high-impact AI/ML projects at scale. Experience mentoring and managing AI/ML teams in collaborative, cross-functional environments. Day-to-Day Activities Direct and oversee AI/ML model development, validation, deployment, and monitoring. Review project designs, provide technical oversight, and conduct code/model reviews. Drive research and experimentation to apply novel AI methods to solve real-world problems. Support proposal development and client engagements with AI/ML subject matter expertise. Foster a culture of continuous learning, innovation, and data-driven thinking. Qualifications Bachelor s or Master s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Relevant certifications (e.g., TensorFlow, AWS Machine Learning, Azure AI Engineer) are a plus. Soft Skills Strong leadership, team management, and mentoring capabilities. Excellent communication and stakeholder engagement skills. Strategic thinking with a passion for innovation and emerging technologies. Ability to thrive in a dynamic, fast-paced environment and lead through ambiguity. Diversity & Inclusion at Synechron Synechron is committed to a diverse and inclusive workplace. Through our Same Difference DEI initiative, we celebrate unique backgrounds and perspectives while fostering a respectful, empowering environment. We welcome applications from candidates of all identities and provide support through mentoring, internal mobility, and flexible work arrangements. Qualification : Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

Role: Senior Analyst Machine Learning Performance & Testing Location: Bengaluru, Karnataka, India Experience: 3 5 Years Employment Type: Permanent, Full-Time About the Role We are seeking a skilled and detail-oriented Senior Analyst with strong experience in ML model performance testing, load testing, and end-to-end (E2E) automation. This role is focused on ensuring scalable, low-latency deployment of production-grade machine learning models. The ideal candidate will be proficient in evaluating model performance under varied workloads, building robust test frameworks, and enhancing system monitoring. Key Responsibilities Conduct load testing and performance benchmarking for machine learning models under varying requests per second (RPS) scenarios. Develop and automate end-to-end test cases to validate model readiness and support smooth rollouts. Monitor and improve model scalability, response time, and error rates across production environments. Collaborate with ML engineers, backend developers, and QA test teams to ensure seamless integration and testing workflows. Identify and address bottlenecks in model inference, helping improve performance for high-volume, low-latency applications. Set up alerting and observability pipelines for model health using industry-standard tools. Required Skills & Tools Performance Testing & Monitoring: ML Load Testing, Job Monitoring, Model Scalability Evaluation Platforms & Tools: Databricks, MLflow, Seldon, Kubeflow, Tecton, Jenkins Cloud Services: Experience with AWS and deploying/testing models in cloud environments Programming Languages: Proficiency in at least one of the following Python, Java, Scala Experience: Working with production-level ML models, especially involving high data volumes and real-time inference Strong communication skills and ability to work in cross-functional teams Preferred Qualifications Hands-on experience with CI/CD pipelines for ML systems Knowledge of A/B testing and canary deployments for ML models Experience building testing frameworks for ML infrastructure at scale Understanding of monitoring and alerting best practices in production ML systems Be at the forefront of ML operations and model performance optimization Collaborate with industry-leading engineers and contribute to cutting-edge AI deployments Gain deep exposure to real-time data systems, cloud platforms, and enterprise-scale ML testing Competitive compensation and an innovative, fast-paced work environment

Job Title: Machine Learning Engineer III Location: Bangalore, India Company: Glance An InMobi Group Company About Glance Founded in 2019, Glance is a cutting-edge consumer technology company operating innovative digital platforms including Glance, Roposo, and Nostra. Our flagship Glance Lock Screen reaches over 450 million smartphones worldwide, delivering personalized, context-driven content without requiring app downloads. Roposo redefines live streaming experiences with creator-led interactive content, and Nostra stands as the largest gaming platform in India and Southeast Asia, offering immersive gaming and social engagement. Headquartered in Singapore, Glance is an unconsolidated subsidiary of InMobi Group. At Glance, we believe in empowering you to dream big, innovate boldly, and own your impact from day one. Collaborate with talented peers on mission-critical projects leveraging bleeding-edge technology to disrupt consumer experiences. Enjoy perks including daily meals, gym access, training sessions, state-of-the-art tech tools, and a family-friendly workspace where your kids and pets are always welcome. Role Overview We are seeking a skilled Machine Learning Engineer III passionate about designing, developing, deploying, and scaling high-impact ML solutions. You will partner closely with data scientists, engineers, and product teams to build end-to-end ML systems, microservices, and APIs that power AI-driven products on Glance s platforms. Key Responsibilities Architect and implement scalable ML solutions to accelerate experimentation, model building, and deployment. Develop microservices and APIs for serving machine learning models and services efficiently. Design, prototype, and build new ML/AI products and proof-of-concepts in collaboration with cross-functional teams. Explore and adopt new platforms, algorithms, and technologies to enhance ML capabilities. Manage project priorities, deadlines, and deliverables while maintaining transparent communication across teams. Take ownership of end-to-end ML engineering lifecycle from research collaboration to production deployment. Preferred Qualifications 5+ years of professional experience as a Machine Learning Engineer with a proven track record of delivering impactful ML solutions. Bachelor s, Master s, or PhD degree in Computer Science, Mathematics, Statistics, or related analytical fields. Deep theoretical and practical knowledge of recommender systems, computer vision (CNNs), GPU optimization, and generative AI models. Proficiency in Python, Golang, Spark, and familiarity with popular data science and ML libraries. Strong background in advanced mathematics, statistics, and algorithmic problem solving. Excellent technical documentation skills and demonstrated leadership in driving cross-functional projects. Experience working in data science or research-oriented roles with a passion for solving complex challenges. Join Glance and contribute to building next-generation AI-driven consumer experiences. Apply now to be part of a visionary tech team in Bangalore! Qualification : Bachelors, Masters, or PhD degree in Computer Science, Mathematics, Statistics, or related analytical fields.

Staff Software Engineer, Machine Learning (Search) Location: Bengaluru, India Company: Databricks Role Overview Join Databricks Applied AI team as a Staff Engineer to lead advancements in Search Quality. This role focuses on improving search ranking, query understanding, and building scalable evaluation frameworks to enhance discovery across millions of data assets on the platform. Key Responsibilities Lead development and deployment of ML/NLP-based search relevance models integrated with Databricks products. Design and build automated ML pipelines for data preprocessing, query understanding/rewrite, ranking, retrieval, and evaluation. Collaborate with product managers and cross-functional teams to drive strategic search product innovations. Develop robust frameworks for offline and online evaluation of search ranking improvements. BS or higher (MS/PhD preferred) in Computer Science or related fields. 10+ years experience building search relevance systems at scale in production or research environments. Experience applying Large Language Models (LLMs) to search relevance problems. Expertise in query understanding, NLP, text mining, recommendations, personalization, discovery, or conversational AI. Strong computer science fundamentals. Contributions to popular open-source projects is a plus. Work at the forefront of AI-driven data products, collaborate with top AI/ML experts, and influence how thousands of organizations discover and interact with data. Databricks offers a cutting-edge platform and a collaborative, innovative culture. Qualification : BS or higher (MS/PhD preferred) in Computer Science or related fields.

Engineering Leader - Machine Learning Location: Bangalore, Karnataka, India Employment Type: Full-Time | Hybrid Work Model About Eightfold.ai At Eightfold.ai, we re revolutionizing the future of employment by leveraging artificial intelligence to connect individuals to the right career opportunities based on their skills, not just their network. Our AI-powered Talent Intelligence Platform is transforming how organizations plan, hire, develop, and retain a diverse workforce. With $410M+ in funding and a $2B+ valuation, we re growing rapidly, and if you're passionate about solving one of society's most critical challenges employment then Eightfold is the place for you. Led by visionary leaders like Ashutosh Garg (former Google Search and Personalization leader) and Varun Kacholia (former Facebook and Youtube leader), we are shaping the future of AI-powered talent management. About the AI Platform Team Our AI/ML team is the heart of Eightfold, pushing the boundaries of applied machine learning. We re working with massive datasets, solving complex problems, and building cutting-edge AI models that are reshaping how companies approach talent management. Join us if you re eager to work in a team where every day presents a new challenge and opportunity. What You ll Do As the Engineering Leader - Machine Learning, you ll be responsible for leading and mentoring a high-performing team of engineers, driving the success of AI-driven products at Eightfold. Your primary responsibilities will include: Team Leadership: Coach, mentor, and manage a talented team of engineers to foster a culture of innovation, collaboration, and high performance. ML Model Ownership: Lead the development and deployment of cutting-edge deep learning models across all Eightfold products, ensuring reliability, scalability, and high-quality performance. Platform Development: Help build high-performance, flexible infrastructure that supports a variety of deep learning techniques and modeling approaches. End-to-End ML Pipeline: Oversee the end-to-end process of building and deploying machine learning models, including creating robust data pipelines that can process unstructured data. ML Framework Implementation: Design and implement an intuitive ML development framework that ensures efficiency and ease of use for data scientists and engineers. Model Fairness: Work with our internal model fairness platform to ensure that we are providing equal opportunity for everyone through responsible ML practices. Cross-Team Collaboration: Work closely with product teams to apply deep learning techniques to solve complex business problems across various domains. What You Should Already Know To be successful in this role, you should have: Strong Foundation in ML & Deep Learning: Expertise in applying Natural Language Processing (NLP) and deep learning solutions to solve real-world problems. Experience with Language Models: Familiarity with advanced language models such as BERT, GPT-3, T5, and others. Academic Background: A BS, MS, or PhD in Computer Science, Data Science, Mathematics, or related fields. Proven ML Experience: Hands-on experience building and deploying machine learning models at scale, particularly in production environments. Programming Expertise: Strong knowledge of ML languages such as Python, C++, Java, R, Scala, and experience with scientific libraries like numpy, pandas, and frameworks like TensorFlow, PyTorch, scikit-learn, etc. Strong ML Theory Knowledge: In-depth understanding of ML theory and experience working with large-scale datasets, data ingestion, and processing systems. Experience with Distributed Systems: Familiarity with distributed systems, including REST APIs, microservices, and data processing frameworks. Metrics-Focused: A passion for building high-quality models that deliver results and metrics-driven outcomes. Nice to Have Real-Time Tech Problems: Experience with real-time processing or low-latency systems. Cloud Environments: Familiarity with cloud platforms like AWS, and experience using cloud-based ML tools. MLOps Tools & Pipelines: Experience with MLflow, Metaflow, or similar tools to streamline ML workflows and operations. Advanced Tech Stack: Familiarity with tools like Spark, MLlib, Databricks, Apache Airflow, etc. Impactful Work: Join a company dedicated to solving one of society's most pressing issues employment. Your work will have a direct impact on individuals' careers around the world. Innovation at Scale: Work with cutting-edge AI and ML technologies to shape the future of talent management. Competitive Compensation: Receive an attractive salary, equity, and comprehensive benefits package (including family medical, vision, and dental coverage). Collaborative Environment: Work in a culture that values transparency, ownership, and collaboration across teams. Hybrid Work Model: Enjoy a hybrid work environment, with flexibility for remote work and in-office collaboration at our Bangalore office. Growth Opportunities: Be part of a rapidly scaling company with vast opportunities for career development and leadership roles. Equal Opportunity Employer Eightfold.ai is an Equal Opportunity Employer. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, or disability. If you are an experienced and visionary leader in Machine Learning, eager to make a lasting impact while solving one of society's most important challenges, we would love to hear from you. Qualification : BS or MS or PhD degree in Computer Science, Data Science or Mathematics

Lead Software Engineer - Backend Location: Bengaluru, India Employment Type: Full-time, Hybrid About Neuron7.ai Neuron7.ai is a rapidly growing AI-first SaaS company that is redefining service intelligence. Backed by top-tier venture capitalists in Silicon Valley and a distinguished group of angel investors, we are recognized as a startup to watch. Our AI-driven platform helps enterprises make accurate service decisions at scale by delivering service predictions in seconds through the analysis of structured and unstructured data. We work across industries, including high-tech devices, manufacturing, and medical devices, enabling service leaders to excel in critical metrics like first-call resolution, turnaround time, and service margins. At Neuron7.ai, you ll be part of an innovative and dynamic team that is shaping the future of service intelligence. We value creativity, collaboration, and a commitment to pushing boundaries. This is your chance to make an impact in a fast-growing startup and work with cutting-edge technology. About the Team As a Lead Software Engineer - Backend, you will play a crucial role in architecting, developing, and optimizing backend systems for our groundbreaking products. You will lead a talented team, collaborating across functions to deliver scalable and high-performance systems. As a leader, you ll also mentor and guide junior engineers to help them grow in their careers. What You ll Do: Backend Systems Design: Lead the design and implementation of scalable, reliable, and high-performance backend systems. Distributed Systems: Develop and optimize distributed systems to handle large-scale traffic and data. System Architecture: Lead the architecture and design of critical components, ensuring robust and efficient solutions. Code Development: Write clean, maintainable, and efficient code that powers our AI-driven platform. Cross-Functional Collaboration: Work closely with product managers, frontend engineers, and other stakeholders to deliver end-to-end solutions. Troubleshooting & Debugging: Solve complex production issues and implement reliable, performance-optimized solutions. Mentorship: Provide guidance and mentorship to junior and mid-level engineers, fostering a collaborative environment. Continuous Learning: Stay updated on the latest trends and advancements in backend development, AI, and distributed systems. What We re Looking For: Experience: Minimum 10 years of professional experience in backend development, with at least 4 years of experience in AI, NLP, or ML. Programming Skills: Expertise in one of the following programming languages: Java, Python, or Golang. Distributed Systems: Proven experience in building and maintaining distributed systems at scale. Cloud Platforms: Familiarity with at least one major cloud platform (Azure, AWS, or GCP). System Design: Strong understanding of system design, architecture patterns, and data structures. Database Knowledge: Experience with relational and NoSQL databases. API Development: Proficiency in developing RESTful APIs and microservices. Security & Performance: Solid understanding of security best practices and performance optimization in backend systems. Problem-Solving Skills: Strong analytical skills with a proven track record of solving complex engineering challenges. Communication: Excellent communication skills with the ability to collaborate across teams and interact with non-technical stakeholders. Preferred Skills: Containerization: Experience with Kubernetes, Docker, or other containerization tools for scalable deployment. Messaging Systems: Familiarity with Kafka, RabbitMQ, or similar messaging systems for real-time data processing. CI/CD: Knowledge of CI/CD pipelines and automation tools to ensure efficient development and deployment. Data Pipelines: Familiarity with data pipelining frameworks such as PySpark, Flink, or similar for real-time processing. What We Do and Value: At Neuron7.ai, we prioritize integrity, innovation, and a customer-centric approach. Our mission is to enhance service decision-making through advanced AI technology, and we are dedicated to delivering excellence in every aspect of our work. Company Perks & Benefits: Competitive salary, equity, and spot bonuses Paid sick leave Latest MacBook Pro for your work Comprehensive health insurance Paid parental leave Work from home or from our vibrant Bengaluru office with hybrid work arrangements Our Commitment to Diversity and Inclusion: Neuron7.ai is committed to fostering a diverse and inclusive workplace. We ensure equal employment opportunities without discrimination based on race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, marital status, or any other characteristic protected by law. If you re excited about building innovative backend solutions and want to work with cutting-edge technologies in a forward-thinking team, we d love to hear from you!

Backend Engineer Location: Bengaluru, Karnataka, India (On-Site) Department: Engineering Employment Type: Full-Time About Sarvam.ai At Sarvam.ai, we re on a mission to bring generative AI to Bharat. Headquartered in Bengaluru and founded by industry-leading AI experts, Sarvam.ai is pioneering India-first, cost-effective, and high-performance AI agents that enable enterprises to unlock new opportunities and deliver deeper customer value. Join us in shaping the future of AI for India and beyond. Role Overview We are seeking a Backend Engineer with strong Python skills to help build the core infrastructure powering our AI-driven voice and generative applications. You ll work at the intersection of high-performance backend systems and machine learning model orchestration, playing a pivotal role in bringing cutting-edge AI into production environments. Key Responsibilities Develop, maintain, and scale backend services and RESTful APIs using Python and FastAPI (or similar frameworks like Flask, Django). Design and implement Retrieval-Augmented Generation (RAG) systems for AI-powered applications. Build data pipelines and orchestrate workflows for ML/AI model deployment. Write clean, modular code following industry best practices including unit testing and code reviews. Collaborate cross-functionally with ML engineers, data scientists, and product teams to integrate AI models into production environments. Optimize database operations for structured and unstructured data using both SQL and NoSQL solutions. Implement CI/CD pipelines and work with version control systems like Git for smooth deployment cycles. Participate in system architecture discussions and contribute to scaling and performance enhancements. Must-Have Skills & Qualifications Education: Bachelor s degree in Computer Science, Engineering, or a related technical field. Programming: Strong proficiency in Python and sound knowledge of programming principles. Web Frameworks: Experience with FastAPI, Flask, or Django. Database Knowledge: Comfortable working with SQL and NoSQL databases. AI & ML Exposure: Understanding of ML model lifecycle, deployment practices, and basic machine learning concepts. RAG Systems: Exposure to Retrieval-Augmented Generation or AI search systems. Version Control: Hands-on experience with Git and Git-based workflows. Analytical Mindset: Strong problem-solving and debugging skills. Teamwork: Excellent communication and collaboration skills. Nice-to-Have (Preferred Experience) Projects: Demonstrated experience building backend applications via academic, freelance, or open-source work. Cloud Experience: Familiarity with AWS, GCP, or Azure services. DevOps Tools: Exposure to Linux, Docker, Kubernetes, and CI/CD pipelines. Open Source: Active GitHub profile or contributions to open-source projects. Work on real-world AI applications impacting millions across India. Be part of a high-caliber team of AI and product engineering experts. Get in early at a fast-growing generative AI startup redefining the future of enterprise AI in India. Opportunity to grow rapidly, take ownership, and drive innovation. Qualification : Bachelors degree in Computer Science, Engineering, or a related technical field.

Backend Engineer - RAG & ML Specialization Location: Bengaluru, Karnataka, India (On-Site) Department: Engineering Employment Type: Full-Time About Sarvam.ai Sarvam.ai is a cutting-edge generative AI startup based in Bengaluru, India, on a mission to make AI accessible and impactful for Bharat. We develop high-performance, cost-effective AI agents tailored to the Indian market, empowering enterprises to unlock new opportunities and create meaningful customer connections. Join us as we reshape AI for India and beyond. Role Overview As a Backend Engineer specializing in RAG (Retrieval-Augmented Generation) systems and Machine Learning (ML) applications, you'll be building scalable backend systems that power AI-driven services. Your work will be critical in developing high-performance platforms for voice and generative AI applications, ensuring secure, scalable, and seamless AI model deployments. Key Responsibilities Backend Development: Design, develop, and maintain scalable, efficient backend applications and RESTful APIs using Python and FastAPI. RAG System Implementation: Build and optimize Retrieval-Augmented Generation (RAG) systems for AI applications, focusing on enhancing AI-driven search and retrieval capabilities. Data Pipeline Management: Develop and manage data pipelines and workflows for integrating AI and ML models into production systems. Code Quality: Ensure adherence to coding best practices, including writing modular code, implementing unit tests, and conducting code reviews. Cross-functional Collaboration: Work closely with AI/ML engineers, data scientists, and other teams to integrate machine learning models into backend systems. Database Optimization: Optimize database queries and efficiently manage both structured and unstructured data. CI/CD Practices: Continuously integrate and deploy code, using version control systems like Git and CI/CD pipelines. System Architecture: Contribute to architectural discussions and improvements, focusing on scalability and performance optimization. Must-Have Skills & Qualifications Educational Background: Bachelor's degree in Computer Science, Engineering, or a related technical field. Programming Skills: Strong proficiency in Python, with a solid understanding of programming fundamentals. Web Frameworks: Experience building backend services using FastAPI, Flask, or Django. Database Knowledge: Familiarity with SQL operations and NoSQL databases for efficient data management. AI & ML Exposure: Hands-on experience with Machine Learning and Deep Learning techniques, and understanding of AI model deployment in production environments. RAG Systems Experience: Prior exposure to Retrieval-Augmented Generation (RAG) architectures, with experience building AI-driven search systems. Version Control: Proficiency with Git and understanding of version control workflows. Problem Solving: Strong analytical and debugging skills to address complex technical challenges. Soft Skills: Excellent communication, collaboration, and problem-solving abilities. Good to Have (Preferred Experience) Backend Projects: Demonstrated experience working on backend applications using Python frameworks (FastAPI, Flask, Django) through academic or personal projects. Cloud Knowledge: Basic understanding of cloud platforms and services such as AWS, GCP, or Azure. DevOps & Containers: Exposure to Linux/Unix environments and containerization concepts (Docker, Kubernetes). CI/CD: Experience setting up CI/CD pipelines for automated testing and deployment. Open Source Contributions: Contributions to open-source projects or a strong GitHub profile showcasing backend development expertise. Impactful Work: Work on groundbreaking generative AI applications that are transforming the future of technology in India. Collaborative Environment: Join a high-performing team of AI experts and engineers, driving innovation and delivering real-world solutions. Growth Opportunities: Be a key player in a fast-growing AI startup, with the opportunity to grow alongside the company. Cutting-edge Technologies: Leverage the latest in AI, Machine Learning, and Cloud Technologies to build state-of-the-art systems. Qualification : Bachelor's degree in Computer Science, Engineering, or a related technical field.

Principal Applied Scientist Location: Bangalore, Karnataka, India Employment Type: Full-Time Overview Join the Computational Advertising Team within the AI & Research organization at Microsoft. We are seeking a passionate Principal Applied Scientist with expertise in machine learning, deep learning, natural language processing, and optimization. The team works on some of the most exciting problems in machine learning, powering the search advertising ecosystem of Bing, which holds a 30% share of desktop search in the US and a significant presence worldwide. The Principal Applied Scientist will contribute to building large-scale machine learning systems that model user responses, ranking, and various other business applications. Your work will have direct business impact, collaborating with top-tier machine learning scientists and engineers to deliver innovative solutions. Key Responsibilities Design & Implement ML Algorithms: Develop, tune, and analyze complex algorithms for large datasets and real-time systems in the advertising ecosystem. Productionize Machine Learning Models: Focus on deploying machine learning models in large-scale production environments, ensuring high-quality and sustainable performance. Collaborate with Experts: Work closely with cross-functional teams of scientists and engineers to integrate advanced machine learning techniques into production systems. Research & Development: Contribute to ongoing research in machine learning, optimization, and information retrieval to advance the core technologies in search advertising. Mentorship & Thought Leadership: Share your expertise with the team, mentor junior scientists, and help shape the direction of research efforts within the team. Qualifications Required Qualifications: Bachelor's degree in Statistics, Econometrics, Computer Science, Electrical Engineering, or related field AND 6+ years of relevant experience (e.g., statistics, predictive analytics, research), OR Master's degree in a related field AND 4+ years of relevant experience, OR Doctorate in a related field AND 3+ years of relevant experience, OR Equivalent experience in machine learning, research, or applied statistics. Additional Requirements: Strong understanding of probability, statistics, machine learning, A/B testing, and optimizing ML models for accuracy. Experience with distributed computing systems (e.g., Hadoop, Spark) for large-scale training and prediction with ML models. Hands-on experience implementing machine learning algorithms from research papers to production systems. Expertise in TensorFlow or PyTorch and deep learning models. Preferred Qualifications: Solid understanding of natural language processing (NLP), information retrieval, and optimization techniques. Experience working with large-scale, real-time systems and databases. Strong track record of delivering machine learning systems to production and optimizing them at scale. Microsoft s mission is to empower every person and organization on the planet to achieve more. At Microsoft, you ll have the opportunity to work with the brightest minds, contribute to cutting-edge AI advancements, and make a significant impact in a growing $100 billion global market. Employee Benefits Industry-leading healthcare coverage Generous paid time off and family leave policies Access to continuous learning and professional development resources Employee discounts and savings programs Opportunities to collaborate with the world s leading AI experts Global networking and community engagement opportunities Microsoft is an equal opportunity employer. We are committed to fostering an inclusive environment where all individuals are treated with respect, regardless of race, gender, religion, disability, or any other characteristic protected by law. Qualification : Bachelor's degree in Statistics, Econometrics, Computer Science, Electrical Engineering, or related field AND 6+ years of relevant experience (e.g., statistics, predictive analytics, research), OR Master's degree in a related field AND 4+ years of relevant experience, OR Doctorate in a related field AND 3+ years of relevant experience, OR Equivalent experience in machine learning, research, or applied statistics.

AI Platform Architect Location: Bangalore, Karnataka, India Employment Type: Full-Time About Adobe Adobe is changing the world through digital experiences. Whether you're an emerging artist or a global brand, our tools empower creativity and innovation across every screen. From powerful imaging and video solutions to immersive web and app design, Adobe s mission is to help people and businesses deliver exceptional digital experiences. We are committed to creating an inclusive workplace where everyone is respected and given equal opportunity. Innovation can come from anywhere and the next big idea could be yours. Job Description We are looking for a visionary AI Platform Architect with deep expertise in building and scaling cloud-native, AI-powered platforms. The ideal candidate will have experience deploying large-scale, customer-facing AI solutions and a deep understanding of modern cloud architecture, data systems, MLOps, and LLMOps. Responsibilities Design and develop scalable AI/ML platforms and pipelines across AWS, Azure, and GCP. Architect end-to-end LLM pipelines including model training, fine-tuning, serving, inference APIs, and monitoring. Lead cross-functional teams in delivering AI solutions from experimentation to production. Implement MLOps and LLMOps best practices using tools like MLFlow, SageMaker, Langchain, and LangGraph. Design GPU-optimized architectures for training and inference of LLMs using DeepSpeed, vLLM, and other modern frameworks. Support infrastructure automation and container orchestration with Kubernetes, Docker, and CI/CD pipelines. Collaborate with internal stakeholders and clients to understand requirements, evangelize platform solutions, and ensure successful delivery. Key Skills and Expertise Cloud and DevOps: Expertise in AWS, Azure, GCP especially VPC design, cloud databases, and serverless architecture. Certified in AWS Professional Solution Architect, AWS ML Specialty, or Azure Solutions Architect Expert (preferred). Proficient with Kubernetes, Docker, FluentD, Kibana, Grafana, Prometheus. Data and Streaming: Experience with OLTP/OLAP databases and cloud-native data warehouses like BigQuery, Aurora, Spanner. Hands-on with Kafka, Apache Flink, Spark, Airflow, Databricks, Apache Iceberg, Presto. AI/ML & LLM Expertise: In-depth understanding of LLMs (GPT, Gemini, Claude, Mixtral, Llama, Hugging Face OSS models). LLMOps frameworks: Langchain, Langgraph, Langflow, Flowise, LLamaIndex. ML lifecycle tools: MLFlow, SageMaker, Vertex AI, Azure AI, AWS Bedrock. Proven experience in model optimization, fine-tuning, and high-throughput inference systems. Programming Languages: Proficient in Python, SQL, and JavaScript. Preferred Qualifications 10+ years in cloud and AI/ML platform architecture roles. Experience delivering AI solutions for enterprise-scale clients. Hands-on experience with GPU architecture and parallel/distributed training. Strong communication skills with ability to influence technical and business stakeholders. Work on cutting-edge AI technologies and shape future product experiences used by millions. Collaborate with world-class engineers and scientists in a diverse, inclusive culture. Be part of a company that values creativity, innovation, and employee well-being. Adobe is proud to be an Equal Opportunity Employer. We welcome and encourage candidates from all backgrounds to apply.