Engineer Production Jobs in Bengaluru

Application Support Engineer I Location: Bangalore Experience: Up to 2+ Years About Tekion Tekion is revolutionizing the automotive industry with the first cloud-native automotive platform, transforming an ecosystem that hasn t seen major innovation in over 50 years. Our Automotive Retail Cloud (ARC), Automotive Enterprise Cloud (AEC), and Automotive Partner Cloud (APC) connect OEMs, dealerships, consumers, and partners through one seamless platform. Leveraging big data, AI, and machine learning, Tekion delivers the best automotive retail experiences across North America, Asia, and Europe. Role Overview We are looking for an enthusiastic Application Support Engineer I who loves challenges, enjoys problem-solving, and is passionate about delivering exceptional customer experiences. You will act as a subject matter expert in your domain, supporting our dealership clients, coordinating technical issues, and ensuring the support team follows processes and delivers solutions effectively. Key Responsibilities Take ownership of customer-reported issues and ensure problems are resolved end-to-end. Research, diagnose, troubleshoot, and identify solutions to resolve system and application issues. Follow standard escalation procedures for unresolved issues and coordinate with internal teams. Understand applications both functionally and technically. Use internal databases and external resources to provide accurate technical solutions. Ensure all issues are properly logged and tracked. Prioritize and manage multiple open issues simultaneously. Prepare accurate and timely reports on support activities. Document technical knowledge in notes, manuals, and knowledge bases. Support rotational shifts as required. Required Skills & Experience 0 2+ years of experience in application, production, or product support. Advanced knowledge of SQL, MongoDB, and basic network configurations. Strong understanding of databases, APIs, and coding fundamentals. Ability to learn and master company-specific software. Strong problem-solving skills and attention to detail. Excellent written and verbal communication skills. Ability to diagnose and address application-related issues effectively. Understanding of IoT and software systems is a plus. Be the first point of contact for dealership clients, ensuring their technical issues are resolved quickly. Play a key role in improving customer satisfaction by providing accurate and timely solutions. Contribute to a knowledge-sharing culture through documentation and process improvements. Work in a collaborative, agile environment alongside cross-functional teams on challenging projects.

ERP Engineer Location: Bengaluru Department: Hardware Employment Type: Full-Time About Dozee Dozee Health AI is a pioneer in AI-powered, contactless Remote Patient Monitoring (RPM) and Early Warning Systems (EWS), driving transformation in healthcare at scale. Headquartered in Bengaluru, Dozee has quickly emerged as India s #1 RPM company. Trusted by leading healthcare providers across India, the USA, and Africa, Dozee s innovative solutions enhance patient safety, improve outcomes, and reduce costs. We aim to Save a Million Lives with Health AI. Role Overview We are looking for an ERP Engineer to manage and optimize Microsoft Dynamics ERP modules, ensuring seamless performance and data integrity across our systems. You will work alongside technical and business teams to implement customizations and integrations that enhance our operational efficiency and scalability. Key Responsibilities ERP Management & Customization Manage and maintain Microsoft Dynamics ERP modules to ensure system stability and optimal performance. Develop and deploy customizations, workflows, and process automations that align with business needs. Integrate ERP with internal systems (CRM, HRMS, Finance) and third-party applications using APIs and data connectors. Collaboration & Implementation Collaborate with cross-functional teams to analyze business requirements and design ERP solutions. Conduct testing, document new features, and support system enhancements. Provide troubleshooting and technical support to ensure minimal system downtime. Training & Optimization Lead end-user training and create user manuals for smooth ERP adoption. Monitor system performance, suggest improvements, and optimize ERP configurations. Work with stakeholders to enhance ERP processes in finance, procurement, inventory, and production. Requirements Experience & Qualifications 3 5 years of hands-on experience with ERP management, customization, and integration. Specific experience with Microsoft Dynamics 365 Business Central / Dynamics NAV is preferred. Bachelor s or Master s degree in a relevant field. Skills Strong understanding of ERP architecture, data structures, and business workflows. Experience with integration tools and middleware such as Azure Integration Services or Power Automate. Familiarity with project management tools like JIRA, Confluence, or Asana. Personal Attributes Strong analytical and problem-solving abilities with high attention to detail. Excellent communication skills and the ability to collaborate with multiple stakeholders. Why Join Dozee Be part of a mission-driven company transforming healthcare with AI. Work with top healthcare providers and cutting-edge technology. Opportunity to drive impactful change in a high-growth, fast-paced environment. Qualification : Bachelors or Masters degree in a relevant field

Security Research Engineer Security Research Experience: 5 8 Years | Location: Bangalore | Employment Type: Full-Time About SecPod SecPod is a SaaS-based cybersecurity products company focused on prevention-first security. Our Saner Cloud platform is a unified CNAPP solution that combines AI-driven threat intelligence, automated vulnerability detection, and Cloud Security Posture Management (CSPM) to secure multi-cloud environments. Role Summary We are seeking a highly skilled Security Research Engineer to join our Security Research team. This role focuses on researching emerging cloud security threats, developing security intelligence feeds, building proof-of-concepts (PoCs) for misconfigurations, and creating automated remediation and compliance content. Key Responsibilities Threat Research: Conduct security research to develop intelligence feeds and checks with a strong emphasis on cloud security. Vulnerability & Risk Analysis: Identify and create PoCs for emerging cloud misconfigurations and security risks. Automation: Develop automation for research and validation tasks using Python or other scripting languages. Compliance & Remediation: Build remediation feeds for cloud misconfigurations and compliance benchmarks. Lifecycle Management: Manage the end-to-end lifecycle of research outputs, from initial development through production release. Required Qualifications & Skills Professional Experience: 5 8 years in security research or engineering, with at least 3 years in a senior technical role. Cloud Infrastructure: Hands-on experience with AWS, Azure, or GCP. Technical Fundamentals: Strong understanding of operating systems, networking, and computer science security. Programming: Proficiency in languages such as Python, C, C++, or Java. Environment Expertise: Experience across Linux/Unix, Windows, and virtualization environments. Compliance: Solid knowledge of cloud security and security benchmark compliance. Education Bachelor s degree (or equivalent) in Computer Science or a related field. Qualification : Bachelors degree (or equivalent) in Computer Science or a related field

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

Lead Software Engineer - Scale & Performance Location: Bengaluru Experience: 6 12 years About VuNet VuNet is a pioneer in Business Journey Observability, using Big Data and Machine Learning to revolutionize digital experiences in the financial services industry. Our platform delivers end-to-end visibility into customer journeys, helping organizations proactively resolve issues, ensure operational resilience, and deliver superior user satisfaction. With over 28 billion digital transactions monitored every month and serving more than 300 million users globally, VuNet is shaping the future of observability for some of the largest banks and financial institutions. We are Series B funded, part of NASSCOM s DeepTech Club, and recognized by global analysts such as Gartner and Omdia. Your Role: Lead Software Engineer - Scale & Performance As a Lead Software Engineer for Scale & Performance, you ll own the performance and scalability benchmarks for VuNet s observability platform. You will work with cutting-edge technologies, design robust test frameworks, and ensure that our platform scales seamlessly to meet the demands of millions of users. Roles & Responsibilities Own performance and scalability benchmarking for key platform components (ingestion pipelines, data storage, and query services). Design and execute load, stress, soak, and capacity tests across microservices, agents, and ingestion layers. Identify and resolve performance bottlenecks in both infrastructure (CPU/memory/IO) and application layers (API latency, throughput, GC behavior). Develop and maintain performance test frameworks, preferably using Kubernetes-based environments. Collaborate with DevOps and SRE teams to optimize system configurations (Kubernetes, Postgres/TimescaleDB, ClickHouse, Kafka) for scale. Implement OpenTelemetry for service instrumentation to monitor system health and latency (p50/p95/p99 metrics). Contribute to capacity planning, scaling strategies (horizontal/vertical), and resource optimization. Analyze production incidents related to scaling issues and drive permanent fixes. Work with engineering teams to design scalable architecture patterns and define SLIs/SLOs for system performance. Document performance baselines, tuning guides, and scalability best practices for internal use. What You Bring Mandatory Skills: Strong background in performance engineering for large-scale distributed systems or SaaS platforms. Expertise in Kubernetes, container runtimes (containerd/Docker), and resource profiling in containerized environments. Solid understanding of Linux internals, CPU/memory profiling, and network stack tuning. Hands-on experience with observability tools (Prometheus, Grafana, OpenTelemetry, Jaeger, Loki, Tempo, etc.). Familiarity with observability platform datastores like ClickHouse, PostgreSQL/TimescaleDB, Elasticsearch, or Cassandra. Experience with performance benchmarking tools such as k6, Locust, JMeter, or custom Golang/Python scripts. Ability to interpret system metrics (CPU usage, memory, GC, latency) and correlate across different layers. Nice-to-Have Skills: Experience with agent benchmarking (OpenTelemetry Collector, custom data shippers). Exposure to streaming systems like Kafka, NATS, or Pulsar. Familiarity with CI/CD pipelines for performance testing and regression tracking. Knowledge of cost optimization and capacity forecasting in cloud environments (AWS/GCP/Azure). Proficiency in Go, Python, or Bash scripting for automation and data analysis. Life at VuNet: At VuNet, we're building a world-class observability platform, and we re just getting started. You ll be part of a passionate, problem-solving team that embraces collaboration, fast learning, and staying ahead of emerging technologies like Gen AI. We foster a high-trust, inclusive culture where collaboration, ownership, and innovation are central to our success. If you're looking to work on cutting-edge tech, make a real impact, and grow with a supportive team you ll fit right in at VuNet. Benefits: Comprehensive health insurance coverage for you, your parents, and dependents. Mental wellness and 1:1 counseling support. A culture that promotes continuous learning, innovation, and career growth. Transparent, inclusive, and high-trust workplace. Opportunities for skill enhancement with training programs focused on new Gen AI technologies.

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.

Staff Software Engineer AI & Automation Location: Bengaluru Company: Okta, The World s Identity Company Experience: 8+ Years Type: Full-Time About Okta Okta is the world s leading identity platform. We empower people to securely access any technology, anywhere, on any device. With products like the Okta Platform and Auth0, we place identity at the core of business security, enabling growth through safe digital transformation. At Okta, we value diverse perspectives and experiences. We believe in learning, collaboration, and building an inclusive environment where everyone belongs. About the Team The Business Technology - Shared Services team is at the forefront of Okta s internal digital transformation. We focus on building intelligent, automated platforms that simplify operations and deliver smarter, faster experiences to both employees and customers. We collaborate across engineering, data science, security, and business units to deliver cutting-edge solutions powered by Generative AI (GenAI), virtual agents, workflow orchestration, and intelligent recommendations. The Opportunity As a Staff Software Engineer, you ll play a critical role in designing and developing AI-powered platforms that drive automation, scale, and intelligence across Okta s business. You ll help make LLM-powered solutions and intelligent automation a reality for the enterprise ensuring performance, security, and reliability at scale. This is a hands-on, individual contributor (IC) role, ideal for engineers who are passionate about solving complex problems, architecting scalable systems, and pushing the boundaries of AI integration. What You ll Do Design & Build: Develop scalable backend services that embed GenAI and automation into core business workflows (e.g., virtual agents, document intelligence, smart routing). Collaborate Across Teams: Work closely with product managers, data scientists, and other engineers from ideation to production. Architect for Scale: Make key architectural decisions around LLM integration, API design, data flow, and observability. Code with Excellence: Write clean, secure, and maintainable code in Python, Java, or similar languages. Build for Production: Use Docker, Kubernetes, and CI/CD pipelines to build and deploy high-availability services. Champion Best Practices: Promote high standards for testing, security, code reviews, and operational readiness. Mentor & Guide: Support a collaborative team culture through peer mentorship and design reviews. What You ll Bring 8+ years of experience in software engineering with a strong track record of building and maintaining production-grade, cloud-native services. Expertise in distributed systems, API development, and cloud infrastructure (AWS, GCP, or Azure). Proficiency in Python, Java, or Go. Experience with Docker, Kubernetes, and observability tools (e.g., Prometheus, Grafana, ELK). Exposure to AI/ML concepts and eagerness to work with LLMs, NLP, or automation platforms. A strong sense of ownership, collaborative mindset, and a bias toward action. Passion for learning and working with emerging technologies especially in the AI and automation space. Why Join Okta Make AI Real: Help move GenAI from experimentation to enterprise-wide impact. Build with Purpose: Work on challenges that simplify and secure Okta s internal operations. Grow in a Human-Centered Culture: Join a humble, technically driven team that values learning, excellence, and personal growth. Join Okta and shape how identity, AI, and automation come together to power the modern enterprise.

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.

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: Production Engineer Department: Production Location: Bengaluru Role Overview: We are seeking a skilled Production Engineer to manage and optimize the operation of press machines within our production facility. The ideal candidate will ensure smooth, efficient production processes by maintaining equipment, troubleshooting issues, and driving continuous improvement in machine performance and product quality. Key Responsibilities: Oversee the day-to-day operation of press machines, ensuring they run efficiently and meet production targets. Perform routine preventive maintenance to keep press equipment in peak operating condition. Troubleshoot and resolve mechanical, electrical, or operational problems promptly to minimize production downtime. Calibrate and adjust machinery to maintain adherence to quality standards and product specifications. Analyze production data to identify opportunities for enhancing press performance, reducing cycle times, and improving product quality. Respond quickly to mechanical and electrical faults, implementing effective corrective measures. Qualifications & Skills: Bachelor s degree (B.E/B.Tech) in Mechanical Engineering or a relevant diploma. Practical experience in machine operation, maintenance, and troubleshooting in a manufacturing environment. Strong problem-solving skills with the ability to diagnose and fix mechanical and electrical issues efficiently. Knowledge of quality standards and machine calibration techniques. Qualification : Bachelors degree (B.E/B.Tech) in Mechanical Engineering or a relevant diploma.

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

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.

Machine Learning Engineer 5 Location: Bangalore, Karnataka, India Employment Type: Full-Time About Adobe Adobe is transforming the world through digital experiences. From individual creators to global enterprises, our tools empower everyone to create stunning visuals, videos, applications, and more. We believe in fostering an inclusive and innovative workplace where ideas can come from anyone, anywhere and the next big breakthrough could be yours. The Opportunity Adobe Express enables users from beginners to professionals to design eye-catching content with ease, powered by advanced AI technologies. At the heart of this mission is the AI Foundations team, which is building modular, reusable AI systems and the Horizon AI Stack to supercharge the Adobe Express experience. As a founding member of this elite team, you will tackle strategic AI challenges and deliver scalable, high-impact solutions. What You ll Do Drive the vision and development of reusable, cloud-scale AI systems for Adobe Express. Collaborate with Adobe Research, Applied AI teams, and engineering stakeholders to align AI capabilities with product strategy. Lead all aspects of ML product development: data pipelines, model development, and quality evaluations. Recruit, mentor, and manage a high-performing team of ML engineers and data scientists. Balance cutting-edge research with business-critical deliverables prototyping new ideas, validating, and scaling them. Foster a culture of innovation, experimentation, and scientific rigor focused on solving customer problems. Ensure engineering excellence in architecture, development, and on-time delivery of AI solutions. Basic Qualifications Bachelor s, Master s, or Ph.D. in Computer Science, Machine Learning, Applied Math, Data Science, or related field. 8+ years of industry experience in machine learning, deep learning, or optimization algorithms. 3+ years of experience managing ML/AI teams in a product-focused environment. Preferred Qualifications Experience working in creative tools, design platforms, or imaging domains. Familiarity with LLMs, Diffusion Models, and generative AI techniques. Proven experience in building large-scale, production-grade ML systems. What You Need to Succeed Demonstrated success in building and managing top-tier ML teams that deliver high-quality solutions. Experience shipping widely adopted AI-driven features to large customer bases. Customer-obsessed with a strong product sense and ability to translate user needs into AI capabilities. Outstanding communication skills able to articulate technical ideas to both technical and non-technical audiences. Strong problem-solving, leadership, and strategic decision-making abilities. Work at the intersection of creativity and AI building technologies that empower millions of users globally. Collaborate with world-class researchers and engineers in a mission-driven, inclusive environment. Enjoy robust career growth, leadership opportunities, and excellent employee benefits. Adobe is proud to be an Equal Opportunity Employer. We believe diversity fuels innovation and we re committed to building an inclusive environment for all employees. Qualification : Bachelors, Masters, or Ph.D. in Computer Science, Machine Learning, Applied Math, Data Science, or related field.

Research Scientist Location: Bangalore, Karnataka, India Employment Type: Full-Time About Adobe Adobe is leading the way in transforming the world through digital experiences. From emerging creators to global enterprises, we empower everyone to bring ideas to life with powerful images, videos, documents, and applications across every platform. Innovation, creativity, and inclusivity are the cornerstones of our company culture where great ideas can come from anyone, anywhere. About Adobe Research Adobe Research is one of the world s premier industrial research organizations, where we invent the future of creativity, documents, and autonomous systems through cutting-edge AI and ML innovation. We blend academic excellence with product-focused impact, shaping how millions interact with Adobe s tools and platforms every day. Areas of Research Focus Natural Language Processing (NLP) Natural Language Generation (NLG) Human-Computer Interaction (HCI) and User Experience (UX) Computer Vision Deep Learning & Machine Learning Artificial Intelligence (AI) Image, Audio, Video, and Multimodal Data Processing Autonomic Systems and Computing Responsibilities Invent, design, and prototype breakthrough AI technologies for next-generation Adobe products. Identify emerging research areas and help shape Adobe s long-term research agenda. Publish your work in top-tier journals and conferences, establishing thought leadership in your field. Collaborate with leading academic institutions and global research communities. Partner with cross-functional teams of engineers, designers, and product managers to bring research innovations to production. Required Qualifications Ph.D. (preferred) or Master s degree in Computer Science, Electrical Engineering, Applied Mathematics, or a related technical field. Proven research excellence with a strong publication record in top-tier conferences or journals. Strong experience in one or more of the following: machine learning, deep learning, NLP, computer vision, or multimodal data processing. Demonstrated ability to solve complex, open-ended problems and innovate under uncertainty. Proficiency in software development and modeling (e.g., Python, PyTorch, TensorFlow, etc.). Excellent communication skills, including scientific writing and presentation abilities. Preferred Qualifications (for Senior Roles) 7+ years of research experience in academia or industry. Experience leading research teams or initiatives with significant real-world impact. Collaborate with world-class scientists and thought leaders. Work on breakthrough research that has direct impact on Adobe products used by millions globally. Enjoy a creative and intellectually rich environment with the freedom to explore your ideas. Publish, present, and build your reputation in the global research community. Competitive compensation, excellent benefits, and flexible work culture. Adobe is an Equal Opportunity Employer committed to building a diverse and inclusive workforce. We welcome candidates from all backgrounds and experiences. Qualification : Ph.D. (preferred) or Masters degree in Computer Science, Electrical Engineering, Applied Mathematics, or a related technical field.

Job Title: Lead Cloud Development Engineer Location: Bengaluru, Karnataka, India Team Overview: Join Cloud Software Group (CSG) as a Lead Cloud Development Engineer in our DaaS (Desktop as a Service) team. You will play a pivotal role in developing and maintaining our Gateway Service, a core component of our DaaS infrastructure. In this role, you ll work with cutting-edge cloud technologies to create a seamless, secure, and high-performance experience for our customers. If you re passionate about cloud technologies and want to make an impact in a fast-growing company, this is the perfect opportunity for you. Job Description: As a Lead Cloud Development Engineer, you will be responsible for leading the design, development, and maintenance of a highly scalable and reliable Gateway Service. You will also focus on ensuring the service meets high standards for performance, security, and availability. Your responsibilities will include collaborating with cross-functional teams, troubleshooting issues, and contributing to the overall evolution of our cloud infrastructure. Key Responsibilities: Design & Development: Lead the design and development of scalable, high-performing Gateway Service, focusing on optimizing performance, security, and availability. Architecture Evolution: Contribute to the architecture of the Gateway Service, evaluating and integrating new technologies and patterns to meet increasing demands. Collaboration: Work closely with architects, leads, and engineers, both within and outside the team, to implement new features and enhancements. Code Reviews & Best Practices: Participate in code reviews, ensuring the implementation of high-quality code and adherence to software development best practices. Quality Assurance: Collaborate with QA engineers to ensure comprehensive testing and validation of new releases. Production Support: Lead troubleshooting efforts for production issues, outages, and customer escalations, working with the support and operations teams to minimize customer impact. Emerging Technologies: Stay current with industry trends and emerging technologies, particularly in cloud computing and microservices. Agile Development: Engage in agile development processes, including sprint planning, daily stand-ups, and retrospectives. Qualifications: Education: B.E/B.Tech or M.Tech in Computer Science or a related field. Experience: At least 8 years of software development experience, with a proven track record of designing, developing, and deploying software/services using C/C++ or Golang. Technical Skills: Strong understanding of networking protocols and security best practices. Solid foundation in Data Structures and Algorithms. Good understanding of cloud platforms such as AWS, Azure, or GCP. Experience with CI/CD pipelines and automation tools. Familiarity with containerization technologies like Docker and Kubernetes. Soft Skills: Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams. About Us: Cloud Software Group is one of the world s largest cloud solution providers, serving over 100 million users worldwide. By joining us, you are helping real people leverage cloud-based solutions to get their work done from anywhere. At CSG, we foster a culture where passion for technology, courage to take risks, and continuous learning thrive. This is an exciting time to be part of the company as we evolve and innovate, making a real difference in how people work. Qualification : B.E/B.Tech or M.Tech in Computer Science or a related field.

Job Title: Site Reliability Engineer (SRE) Cloud Platform & Production Pipeline Initiatives Location: Bangalore, India (Office-based role) About Couchbase: As industries race to embrace AI, traditional database solutions fall short of rising demands for versatility, performance, and affordability. Couchbase is leading the way with Capella, the developer data platform for critical applications in our AI-driven world. By uniting transactional, analytical, mobile, and AI workloads into a seamless, fully managed solution, Couchbase empowers developers and enterprises to build and scale applications with unmatched flexibility, performance, and cost-efficiency from cloud to edge. Trusted by over 30% of the Fortune 100, Couchbase is unlocking innovation, accelerating AI transformation, and redefining customer experiences. Come join our mission! Job Overview: As a Site Reliability Engineer (SRE), you will play a pivotal role in managing, optimizing, and maintaining Couchbase s cloud infrastructure for Capella, our Database as a Service (DBaaS) platform. You will be responsible for ensuring the reliability and performance of our cloud service while collaborating closely with engineering teams to improve deployment pipelines, security practices, and overall system health. You will work across cloud platforms and multiple tools to provide guidance, mentorship, and contribute to the strategic direction of cloud operations. Responsibilities: Infrastructure Management: Manage, monitor, and maintain the infrastructure for Capella to ensure reliable operations. Security & Compliance: Implement and manage cloud environments in accordance with company security guidelines, including vulnerability management, penetration testing, and compliance requirements (SOC 2, PCI-DSS, GDPR, HIPAA, etc.). CI/CD & Release Pipeline: Collaborate with engineering teams to optimize CI/CD processes, aiming for a highly resilient deployment strategy, ideally with zero downtime. Cloud Optimization: Stay up-to-date with new technologies and industry trends to continuously improve cloud platform architecture and meet the evolving needs of the business. Security Integration: Work with development teams to integrate security scanners within the DevOps lifecycle, enhancing security posture. Leadership & Mentorship: Provide guidance on architecture, code reviews, and technical feedback to improve service reliability, security, cost, and performance. Incident Management: Demonstrate exceptional problem-solving skills, proactively identifying and addressing potential issues before they affect business operations. Collaboration: Partner with development teams, application owners, and stakeholders to integrate best practices and ensure seamless service delivery. Requirements: Experience: 5+ years in Site Reliability Engineering (SRE), DevSecOps, or similar roles, with significant experience working in public cloud environments. Programming & Scripting: Proficiency in languages such as Go, Python, Java, or Ruby. Linux Expertise: High proficiency with Linux operating systems. Kubernetes Management: Experience in managing and maintaining Kubernetes clusters (both self-managed and managed platforms like AWS EKS). Security & Vulnerability Management: In-depth knowledge of security tools and practices (vulnerability management, pen testing, SCA, DAST, SAST), with hands-on experience using tools like Sysdig, Synk, and Blackduck. Cloud Platforms & Tools: Strong experience with cloud platforms (AWS, GCP, Azure) and open-source tools like Artifactory, Jira, Jenkins, Grafana, Prometheus, Datadog, Thanos, etc. Configuration Management: Proficiency with Terraform, Git, and CI/CD platforms (e.g., CircleCI, GitHub, Spinnaker). Networking Security: Solid understanding of TCP/IP, DNS, HTTP, Firewalls, VPNs, and other networking security concepts. Preferred Skills: Availability & Reliability: Knowledge of SLO/SLA, availability, reliability, and performance concepts. Incident Management: Experience with on-call rotations and incident management. Database Experience: Familiarity with databases, particularly Couchbase. Security Certifications: Relevant certifications in security or cloud technologies are a plus. Couchbase reimagines database technology to deliver a fast, flexible, and affordable cloud database platform, empowering developers to build applications with exceptional customer experiences. Trusted by over 30% of the Fortune 100, Couchbase drives innovation and customer success through its Capella platform. Benefits at Couchbase: Generous Time Off Program: Flexibility to care for yourself and your family. Wellness Benefits: Access to world-class medical plans, dental, vision, life insurance, and employee assistance programs. Financial Planning: RSU equity program, ESPP, retirement planning, and business travel insurance. Career Growth: Focused on your career development and success. Fun Perks: Ergonomic and comfortable office setup, food & snacks for in-office employees, and more!

About the Job Join us as a Generative AI Engineer, where you ll design and develop cutting-edge AI-powered solutions that redefine creativity and innovation. Your work will push the boundaries of what s possible in content generation, from text and images to audio and beyond. In this job, you will: Research & Development: Stay up-to-date with the latest advancements in generative AI and deep learning. Contribute to the development of novel models, exploring innovative algorithms and methodologies. Model Architecture: Design custom generative models using neural network architectures like GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and others tailored for specific applications. Data Processing: Prepare and preprocess large-scale datasets for model training. Apply techniques like data augmentation, normalization, and transformation to improve performance. Training & Optimization: Train generative models using frameworks like TensorFlow and PyTorch, optimizing for efficiency, speed, and quality. Hyperparameter Tuning: Fine-tune models for optimal performance, balancing convergence speed, stability, and output diversity. Evaluation Metrics: Develop metrics to assess the quality, diversity, and novelty of generated content. Continuously iterate and improve models based on these metrics. Deployment: Work with software engineers to integrate generative models into production systems, ensuring scalability, reliability, and performance. Collaboration: Partner with data scientists, machine learning engineers, designers, and product managers to translate business requirements into generative AI solutions. Documentation: Document research, experiments, and codebase thoroughly for internal use and external stakeholders. Continuous Learning: Stay informed on emerging technologies, attend industry events, and contribute to ongoing innovation. Qualifications Bachelor s, Master s, or Ph.D. in Computer Science, Engineering, or related fields. Strong foundation in machine learning, deep learning, and neural networks. Proficiency in Python and relevant AI libraries (e.g., TensorFlow, PyTorch). Hands-on experience with generative models like GANs, VAEs, and their practical applications. Solid understanding of data preprocessing, feature extraction, and model evaluation. Experience training and optimizing neural networks on large-scale datasets. Familiarity with cloud computing and distributed systems (AWS, Azure, GCP) is a plus. Strong problem-solving skills and a creative mindset. Excellent communication and teamwork abilities. A portfolio of generative AI projects or publications is a strong advantage. About Gramener We create software that tells data stories. For example: We advised a global computer manufacturer to focus on order delivery time, increasing NPS by 18% and generating incremental revenue of >$50M. We helped a foundation predict mosquito release points, reducing the process time from 3 weeks to 2 hours in their mission to protect 100M lives from malaria over 5 years. We re good at what we do, which is why we re growing 40% year-over-year. We re looking for passionate innovators to help us scale further. First-hand experience with C-suite-focused business advisory in data & analytics. Opportunities to collaborate with data science experts, domain champions, and client teams, being part of transformative change. A chance to experiment, take risks, and solve meaningful problems. Supportive colleagues and a dynamic environment you ll love working in. Key Metrics for Success Solution quality and business value delivered to clients. Successful project deliveries. Customer satisfaction on engagements. Qualification : Bachelors, Masters, or Ph.D. in Computer Science, Engineering, or related fields.