Machine Learning Frameworks 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

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

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

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

Position: Manager - Analytics Location: SEZ4, Bangalore, Karnataka, India Department: Advanced Analytics Employment Type: Subexian Experience Required: 6 to 9 years Job Overview: We are seeking an experienced Manager - Analytics to lead a team of talented data scientists in delivering impactful data-driven solutions. The ideal candidate will have a solid background in analytical methodologies, including machine learning, statistical modeling, and business analytics. You ll be responsible for collaborating with business stakeholders, driving the design and development of advanced analytics models, and ensuring the delivery of high-quality insights that support strategic decision-making. Key Responsibilities: Analytical Methodology: Research, evaluate, and implement new analytical methodologies and approaches to build innovative data-driven solutions. Utilize a blend of mathematics, statistics, machine learning, and business knowledge to solve complex problems. Business Collaboration: Work closely with business leaders and data owners to define key problems and challenges, ensuring the solutions developed have a significant impact on the business. Team Leadership: Lead and mentor a team of junior data scientists, guiding them through the development, deployment, and refinement of machine learning models in a production setting. Advanced Modeling: Utilize a wide range of analytical models, including reliability models, Markov models, stochastic models, Bayesian modeling, classification models, neural networks, and more to address business challenges effectively. Hands-On Expertise: Apply strong hands-on skills in R and Python, using libraries such as NLTK and Sklearn for developing machine learning models and data analysis. Large Data Management: Work with large datasets and distributed computing frameworks like MapReduce, Hadoop, and Hive, ensuring scalable and efficient data processing. Continuous Improvement: Stay up to date with the latest advancements in analytics and machine learning, continually enhancing models and methodologies to deliver cutting-edge insights. Required Technical Skills: Hands-on Experience in Python & R: Strong proficiency in R and Python programming, with experience in libraries such as NLTK, Sklearn, and other machine learning frameworks. Advanced Statistical & Machine Learning Techniques: Proven expertise in at least one of the following: Reliability models Markov Models Stochastic models Bayesian Modelling Classification Models Cluster Analysis Neural Networks NLP (Natural Language Processing) Deep Learning Non-parametric Methods Multivariate Statistics Big Data Tools: Experience working with large datasets and distributed computing platforms such as MapReduce, Hadoop, Hive, etc. Soft Skills: Leadership & Collaboration: Strong leadership skills with the ability to mentor a team of junior data scientists. Excellent collaboration and communication skills to work with business and technical teams. Problem-Solving & Critical Thinking: Ability to approach complex business problems analytically and come up with data-driven solutions. Continuous Learning: A passion for staying up to date with the latest trends and advancements in analytics, machine learning, and data science. At Subex, you ll have the opportunity to work on cutting-edge projects that make a tangible impact on the business. If you're passionate about leading analytics teams and leveraging data science to drive business success, we would love to have you on board.

Position: Data Architect Location: Remote/Hybrid | Bengaluru, IND We're searching for a highly skilled and experienced Data Architect to join our team. If you have a deep understanding of big data technologies and extensive experience with Hadoop, Python, Snowflake, and Databricks, you're the ideal candidate. You'll be responsible for designing, implementing, and managing complex data architectures that support our critical business needs and objectives. What You'll Do: Design & Architecture Leadership: Design scalable and efficient data architecture solutions that meet current and future business data needs. Lead the development of data models, schemas, and databases, ensuring alignment with business requirements. Architect and implement robust data solutions on leading cloud platforms (AWS, Azure, or GCP). Data Management & Governance: Develop and maintain robust data pipelines and ETL processes using Hadoop, Databricks, and other essential tools. Oversee data integration and quality efforts to ensure consistency and reliability across the organization. Implement data governance best practices, focusing on data security, privacy, and compliance. Collaboration & Mentorship: Work closely with data engineers, data scientists, and business stakeholders to translate data requirements into effective technical solutions. Provide technical leadership and mentorship to junior data engineers and architects. Collaborate with cross-functional teams to ensure data solutions align perfectly with overall business goals. Optimization & Innovation: Optimize existing data architectures for peak performance, scalability, and cost-efficiency. Monitor and troubleshoot data systems to ensure high availability and reliability. Continuously evaluate and recommend new tools and technologies to improve our data architecture. What You'll Bring: Experience: 10+ years in data architecture, data engineering, or a related field. Big Data Expertise: Proven experience with Hadoop ecosystems (HDFS, MapReduce, Hive, HBase). Programming Prowess: Strong programming skills in Python for data processing and automation. Data Platform Mastery: Hands-on experience with Snowflake for data warehousing and Databricks for analytics. Cloud Fluency: Extensive experience with cloud platforms (AWS, Azure, GCP) and their data services. Data Modeling: Familiarity with data modeling tools and methodologies. Core Skills: Deep understanding of big data technologies and distributed computing. Strong problem-solving skills to design solutions for complex data challenges. Excellent communication skills, able to explain complex technical concepts clearly to diverse audiences. Proficient in SQL and database performance tuning. Experience with CI/CD pipelines and automation in data environments. Education: Bachelor's degree in Computer Science, Information Technology, or a related field. Preferred Qualifications: Advanced Degree: A Master's degree in a related field. Cloud Certifications: Certifications like AWS Certified Data Analytics, Google Professional Data Engineer, or Microsoft Certified: Azure Data Engineer Associate. Additional Languages: Experience with other programming languages like Java or Scala. Machine Learning Integration: Knowledge of machine learning frameworks and their integration with data pipelines.

Job Title: Software & Algorithm Design Engineer Robotics Location: Bengaluru Overview: We are seeking a talented Software and Algorithm Design Engineer to join our Robotics team. The ideal candidate will have a strong foundation in machine learning, computer vision, and image processing, coupled with practical experience in developing and optimizing algorithms for real-world robotics applications. This role demands proficiency in C++, familiarity with GPU computing, and a systems-level approach to problem-solving. Key Responsibilities: Develop and model new Machine Learning architectures and algorithms from the ground up. Apply expertise in machine vision and image processing to solve complex robotic perception problems. Classify and evaluate various ML models, understanding their benefits, limitations, and evolution. Parameterize problems with a clear understanding of system-level and process-level impacts. Translate and optimize DSP and/or Neural Network-based algorithms for high performance. Build robust test frameworks to validate algorithm correctness and performance. Collaborate closely with cross-functional teams to deliver production-ready, reliable robotics software beyond prototyping stages. Document code and algorithm design meticulously to ensure maintainability and clarity. Utilize GPU technologies, including CUDA, to accelerate algorithm performance. Required Skills & Qualifications: Strong grasp of Machine Learning fundamentals and practical ML toolkits. Proficient in C++ (Python proficiency assumed). Solid background in Machine Vision and Image Processing. Understanding of control systems is a plus. Familiarity with GPU application development and CUDA programming (expert level not required). Experience optimizing algorithms related to DSP or Neural Networks. Skilled in building comprehensive test frameworks for software validation. Passionate about documentation and writing clean, readable code. Comfortable working within a software development lifecycle to create production-quality software. Preferred Knowledge: ML Architectures and Neural Networks Digital Image Processing & Machine Vision CPU and GPU Architectures CUDA and GPU Programming Basic Software Design Patterns Memory Architecture & Optimization Techniques Algorithm Performance Optimization Tools & Technologies: C++ CUDA cuDNN and other machine learning frameworks Computer Vision libraries (e.g., OpenCV)

Job Title: Robotics Solution Engineer Location: Bengaluru Key Focus Areas: The ideal candidate will have experience and expertise in 40-60% of the following domains: Task Development: Breaking down complex robotic tasks (e.g., pick, orient, place) and designing efficient workflows. Simulation and Validation: Using advanced physics-based simulation tools to model and validate robotic systems and interactions. System Integration: Seamless integration of hardware, software, and sensors tailored to customer environments. Customer-Centric Solutions: Customizing robotic solutions to fit specific customer requirements and constraints. Foundational R&D and ML Development: Supporting research and machine learning algorithm development to enhance robotic perception, autonomy, and decision-making. Roles and Responsibilities: Physics-Based Simulation Development: Develop comprehensive physics-based models for robots, environments, and their interactions. Create and validate dynamic models involving rigid body dynamics, contact physics, material properties, and compliance, especially for multi-arm robotic systems. Build and maintain digital twins of physical robots and real-world environments. Algorithm Development & Implementation: Design, implement, and validate control and motion planning algorithms for multi-arm robots, focusing on manipulation and grasping. Optimize kinematics, dynamics, and force-based control strategies for real-time robotic applications. Support learning-based algorithm implementation for real-time perception and manipulation, including simulation-based testing and validation. Machine Learning Applications: Apply machine learning techniques to robotic perception and decision-making. Implement learning-based algorithms for perception and manipulation tasks. Testing, Validation & Optimization: Develop protocols to validate simulation accuracy by bridging virtual and real-world performance. Create automated test sequences and metrics for robust validation across various scenarios. Analyze simulation results to enhance system performance, safety, and reliability, suggesting design improvements. Collaboration & Cross-Functional Support: Work closely with controls engineers to validate and tune control systems in simulation. Collaborate with algorithm, software, and hardware teams to refine systems and resolve issues. Provide insights from simulation analyses to guide product improvements. Documentation & Reporting: Document simulation approaches, assumptions, and validation outcomes clearly. Prepare detailed reports on system performance, testing results, and optimization opportunities. Skills and Experience: Core Expertise: Advanced physics-based modeling and numerical simulation techniques. Deep understanding of robot kinematics, dynamics, and control theory. Experience with simulation validation and verification methodologies. Sensor modeling for cameras, force/torque sensors, etc. Motion planning algorithm knowledge. Familiarity with machine learning frameworks (PyTorch, TensorFlow) and real-time control implementation. Software & Tools: Experience with physics simulation platforms like NVIDIA Isaac Sim/Omniverse, CoppeliaSim, Mujoco, PyBullet, PhysX, Gazebo, or equivalents. Proficient in Python and C++ for scripting and automation tasks. Comfortable integrating CAD software and managing version control with Git. Engineering & Analysis: Skills in system dynamics modeling and error analysis. Developing test plans and performing root cause analysis. Conducting feasibility studies and model validation. Required Qualifications: Bachelor s or Master s degree in Robotics, Mechanical Engineering, or related fields. Minimum 3 years of professional experience in robotics engineering, with a focus on simulation and modeling. Strong foundation in robot kinematics, dynamics, and control systems. Proficient in Python and C++ programming. Experience with physics engines (PhysX, Bullet, PyBullet) and validating simulation results with real-world data. Preferred Qualifications: Master s or PhD in Robotics, Computer Science, or a related discipline. Hands-on experience with NVIDIA Isaac Sim/Omniverse or similar simulation platforms. Background in computer graphics, sensor modeling, and digital twin technologies. Qualification : Bachelors or Masters degree in Robotics, Mechanical Engineering, or related fields.

Job Title: Senior Manager Data Science, Data Modelling & Analytics Location: Bengaluru Department: Insights & Analysis About the Role: As a Senior Manager, you will lead a team of data scientists and analysts, driving the development and deployment of advanced analytics solutions that enable data-driven decision-making. This role blends strategic leadership with hands-on technical expertise, playing a critical part in delivering impactful insights and analytics across the organization. Key Responsibilities: Hands-On Technical Contribution: Design, develop, and deploy advanced machine learning models and statistical analyses to address complex business challenges. Utilize Python, R, SQL, and other tools to manipulate data and build predictive models. Manage end-to-end data pipelines including collection, cleaning, transformation, and visualization. Collaborate with IT and data engineering teams to integrate analytics solutions into production environments. Provide thought leadership on analytics solutions and metrics aligned with business needs. Team Leadership & Development: Lead, mentor, and manage a team of data scientists and analysts, fostering collaboration and innovation. Guide career development, conduct performance evaluations, and promote skill enhancement. Encourage continuous learning and adoption of best practices in data science methodologies. Strategic Planning & Execution: Collaborate with senior leadership to define and execute data science strategy aligned with business goals. Identify and prioritize high-impact analytics projects that deliver business value. Ensure timely and quality delivery of analytics solutions balancing scope and resources. Client Engagement & Stakeholder Management: Act as primary point of contact for clients, translating business challenges into data science solutions. Lead client presentations, workshops, and discussions, effectively communicating complex analytical concepts. Build and maintain strong client relationships, managing expectations and deliverables. Deliver regular reports and dashboards to senior management and stakeholders. Bridge communication between technical teams and business units to align analytics initiatives with organizational objectives. Cross-Functional Collaboration: Work closely with Business Intelligence, Market Analytics, and Data Engineering teams to integrate analytics into business processes. Translate complex insights into actionable recommendations for non-technical stakeholders. Facilitate data-driven workshops and presentations across the organization. Collaborate with support functions to provide timely leadership updates on operational metrics. Governance & Compliance: Ensure compliance with data governance policies and data privacy regulations (e.g., GDPR, PDPA). Implement best practices for data quality, security, and ethical analytics use. Stay abreast of industry trends and regulatory changes affecting data analytics. Qualifications: Education: Bachelor s or Master s degree in Data Science, Computer Science, Statistics, Mathematics, or related field. Experience: 12+ years in advanced analytics, data science, data modelling, machine learning, or related fields. 5+ years in leadership roles managing analytics teams and projects. Experience in BFSI, Hi-Tech, Retail, or Healthcare industries preferred. Experience with media data is a plus. Technical Skills: Proficiency in Python, R, SQL. Experience with data visualization tools like Tableau, Power BI. Familiarity with big data platforms (Hadoop, Spark) and cloud services (AWS, GCP, Azure). Strong knowledge of machine learning frameworks and libraries. Soft Skills: Excellent analytical and problem-solving skills. Strong communication and interpersonal abilities. Ability to influence and drive organizational change. Strategic thinker focused on business outcomes. Desirable Expertise: Advanced Analytics Techniques: Descriptive Analytics: Statistical analysis, data visualization. Predictive Analytics: Regression, time series forecasting, classification, market mix modelling. Prescriptive Analytics: Optimization, simulation modelling. Text Analytics: NLP, sentiment analysis. Machine Learning Techniques: Supervised Learning: Linear/logistic regression, decision trees, random forests, gradient boosting, SVMs. Unsupervised Learning: Clustering, PCA, anomaly detection. Reinforcement Learning: Q-learning, deep Q-networks. Generative AI & Large Language Models (Good to Have): Experience with GPT, Gemini, LLAMA, etc. for text generation, summarization, conversational agents. Hyperparameter tuning, prompt engineering, embeddings, fine-tuning. Additional Skills: Proficiency with Tableau or Power BI (advanced visualization). Strong data management, structuring, and harmonization skills.

Data Scientist Experience: 5+ Years Location: Bangalore, Karnataka, India Job Type: Full Time Job Summary We are seeking an experienced Data Scientist with over 5 years of expertise to join our innovative team in Bangalore. The ideal candidate will have hands-on experience in advanced statistical methods, machine learning, and deep learning frameworks, combined with strong skills in deploying models at scale. Key Responsibilities Apply advanced Statistics and Operations Research methods to solve complex business problems. Develop and deploy predictive and machine learning models using frameworks such as PyTorch, TensorFlow, Keras, and XGBoost. Utilize data engineering and big data tools including PySpark, Databricks, and Flask for building scalable data solutions. Implement and fine-tune NLP models like RNN, LSTM, and attention-based architectures, leveraging pre-trained models from Stanford, IBM, Azure, and OpenAI. Design and optimize efficient SQL queries to extract data from large databases. Work with visualization tools like D3.js, Dash Plotly, and deploy interactive dashboards using Streamlit. Utilize graph databases such as Neo4j for complex data relationships. Manage version control with tools like GitHub or Bitbucket. Deploy machine learning models into production environments using MLOps practices on cloud platforms such as AWS or Azure. Required Skills 5+ years of professional experience as a Data Scientist or similar role. Strong foundation in statistics, machine learning, and deep learning techniques. Proficient in Python-based data science libraries and frameworks. Hands-on experience with cloud-based MLOps and deployment. Excellent SQL skills for data extraction and manipulation. Experience with version control systems and collaborative development. Familiarity with NLP techniques and modern pre-trained language models. Strong problem-solving and communication skills. Qualifications Any graduate degree in Computer Science, Statistics, Mathematics, Engineering, or related field. Join a forward-thinking company in Bangalore, where you will work with cutting-edge technologies to create impactful data-driven solutions. Grow your career in an environment that values innovation, diversity, and continuous learning.

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.

Job Title: Staff Machine Learning Engineer Location: Bengaluru, Karnataka, India Job Type: Full-Time (Hybrid Work Model) Experience Level: 6-10+ Years About Eightfold.ai: At Eightfold.ai, we re revolutionizing the way organizations find, manage, and empower talent. As a leader in AI-driven HR tech, our groundbreaking platform is transforming industries by using artificial intelligence to solve talent management challenges at scale. We are looking for exceptional engineers to join our team and be at the forefront of innovation in the field of AI. About the AI/ML Team: The AI/ML team at Eightfold is passionate about building cutting-edge solutions and pushing the boundaries of applied machine learning. We work with massive datasets and tackle complex, real-world challenges to develop state-of-the-art AI models. Our models are transforming how companies approach talent management, and we are looking for a Staff Machine Learning Engineer to help lead this journey. What You Will Do: As a Staff Machine Learning Engineer, you will play a critical role in leading and inspiring our ML team while architecting and implementing scalable, robust ML pipelines for our core products. Lead and Inspire: Mentor and guide a team of talented ML engineers, fostering a collaborative environment that encourages innovation. Architect and Implement: Design and build scalable ML pipelines that power Eightfold s core products. Innovate and Optimize: Develop novel algorithms and continuously enhance the performance, accuracy, and scalability of our models. Solve Complex Problems: Work on challenging real-world problems, including NLP, recommendation systems, and predictive analytics. Stay Ahead of the Curve: Research and implement cutting-edge techniques in deep learning, reinforcement learning, and other emerging fields. LLM & NLP Expertise: Design and implement scalable solutions using Large Language Models (LLMs), fine-tuning them for specific NLP tasks, and developing LLM-powered applications. What You Bring: Required Skills & Experience: Deep Expertise in ML & AI: Strong foundation in Machine Learning, Deep Learning, and Natural Language Processing (NLP) with a proven track record of developing and deploying ML models at scale. Technical Leadership: Experience leading and mentoring teams, with excellent communication and collaboration skills. Problem-Solving Mindset: Ability to analyze complex problems and develop innovative solutions. Passion for AI: Genuine enthusiasm for pushing the boundaries of AI and its real-world applications. Advanced Skills in Python & ML Frameworks: Proficiency in Python and relevant ML frameworks (TensorFlow, PyTorch), along with experience in big data technologies like Hadoop and Spark. CS Fundamentals & Coding: Strong foundation in computer science fundamentals and coding languages (Python, C/C++, Java, Scala, R). GenAI & LLM Expertise: Experience in developing and deploying LLM-powered applications, with knowledge of LLM fine-tuning techniques, optimization strategies, and ethical considerations. Nice to Haves: 6-10+ years of experience in Machine Learning and AI. MS or PhD in Computer Science or related field. Publications in top-tier AI conferences. Contributions to open-source ML projects. Familiarity with Generative AI (GenAI), Transformers, and LLMs. Impactful Work: Play a pivotal role in shaping the future of AI and its applications in talent management. Innovative Environment: Work on cutting-edge projects with world-class experts in the field of AI/ML. Career Growth: Accelerate your career in a dynamic, fast-paced environment with abundant opportunities for professional growth. Hybrid Work Model: Embrace a flexible work environment with the ability to collaborate remotely and in-person at our Bengaluru or Noida offices twice a week starting February 1, 2024. Competitive Benefits: Comprehensive family medical, vision, and dental coverage, a competitive base salary, equity awards, and discretionary bonuses or commissions. How to Apply: If you're a passionate AI/ML engineer ready to take on challenging problems and make a meaningful impact, we d love to hear from you. Join Eightfold.ai and help shape the future of AI-powered talent intelligence! Qualification : MS or PhD in Computer Science or a related field

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

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.

Machine Learning Engineer - Speech AI (ASR & TTS) Location: Bengaluru, Karnataka, India (On-Site) Department: Engineering Employment Type: Full-Time About Sarvam.ai Sarvam.ai is a pioneering generative AI startup headquartered in Bengaluru, India. We specialize in leading transformative research and development in speech and language technologies. Focused on building state-of-the-art ASR (Automatic Speech Recognition) and TTS (Text-to-Speech) models, particularly for Indic languages, we aim to redefine human-computer interaction with cutting-edge, AI-driven solutions. Join us as we push the boundaries of Speech AI to create inclusive, scalable, and intelligent voice-based applications for diverse communities worldwide. Role Overview We are seeking an experienced Machine Learning Engineer specializing in Speech AI (ASR & TTS). The ideal candidate will work on deep learning-based ASR and TTS models, improving accuracy, efficiency, and multilingual capabilities while deploying them at scale. The role involves developing and optimizing speech recognition and synthesis models with a focus on low-resource languages, real-time inference, and scalability. If you have a passion for speech processing and deep learning, this is a great opportunity to make a significant impact in a rapidly growing field. Key Responsibilities ASR (Automatic Speech Recognition) Develop, train, and optimize speech-to-text models using state-of-the-art architectures like Wav2Vec, Whisper, Conformer, and DeepSpeech. Implement techniques for low-latency ASR inference, including beam search, language model integration, and real-time transcription. Improve speech recognition accuracy for low-resource languages, especially Indic languages, using transfer learning and data augmentation. Optimize ASR pipelines for noise robustness, speaker adaptation, and domain-specific transcription. TTS (Text-to-Speech) Develop and fine-tune neural TTS models such as Tacotron, FastSpeech, VITS, or WaveNet for high-quality, natural-sounding speech synthesis. Implement multilingual and expressive TTS models with prosody and emotion control. Optimize TTS inference for deployment on edge devices, mobile, and cloud platforms. Improve speech synthesis quality through voice cloning, neural vocoders (HiFi-GAN, WaveGlow), and prosody modeling. General Speech AI Responsibilities Benchmark and profile ASR/TTS models to improve latency, efficiency, and deployment performance. Deploy scalable speech AI APIs on AWS, Azure, or GCP for real-world applications. Optimize ASR & TTS models for edge and offline inference. Stay updated with the latest advancements in speech AI, neural vocoders, and real-time inference techniques. Must-Have Qualifications Experience: 2-3 years of experience in speech AI, deep learning, or machine learning, with a focus on ASR & TTS. Education: Bachelor s or Master s degree in Computer Science, AI/ML, Speech Processing, or a related field. ML Frameworks: Proficiency in PyTorch or TensorFlow for training and deploying ASR/TTS models. ASR Expertise: Experience with speech-to-text architectures like Whisper, Wav2Vec, Conformer, or DeepSpeech. TTS Expertise: Experience with speech synthesis models like Tacotron, FastSpeech, or VITS. Speech Signal Processing: Understanding of MFCCs, STFT, phonemes, prosody modeling, and feature extraction. Inference Optimization: Hands-on experience with TensorRT, ONNX, or quantization (INT8, FP16) for ASR/TTS. Cloud & Edge Deployment: Experience deploying speech models on AWS, GCP, or Azure. Preferred Qualifications Experience with speech diarization, speaker recognition, or language modeling for ASR. Familiarity with zero-shot TTS, voice cloning, and multilingual speech modeling. Understanding of CUDA optimization and low-bit quantization for ASR/TTS models. Contributions to open-source speech AI projects or a strong GitHub portfolio showcasing relevant work. Experience with real-time streaming ASR/TTS applications and low-latency inference. Innovative Impact: Work on AI-driven speech solutions that are changing how people interact with technology, especially in low-resource languages. Cutting-Edge Technology: Contribute to the development of state-of-the-art speech AI models in a rapidly advancing field. Collaborative Environment: Work with a team of experts in AI, machine learning, and speech processing, in a startup culture. Growth Opportunities: Sarvam.ai offers exciting career growth in a fast-paced environment with opportunities for personal and professional development. Interested candidates are invited to submit their resume, cover letter, and any relevant project portfolios or GitHub links showcasing their experience in ASR, TTS, or Speech AI. Strong AI-related projects, whether in industry, research, or personal work, will be highly valued. Qualification : Bachelors or Masters degree in Computer Science, AI/ML, Speech Processing, or a related field.

Gen AI Engineer - L1 | Bengaluru, India About Wipro Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a global IT consulting and services company with over 230,000 employees across 65 countries. We offer innovative solutions in consulting, engineering, and operations to solve complex digital transformation challenges. Role Overview We are looking for an experienced Gen AI Engineer - L1 with deep expertise in Generative AI, LLMs, RAG pipelines, and Python-based machine learning frameworks. The role will focus on developing secure, scalable AI systems using modern tools and cloud platforms. Key Responsibilities Design, implement, and optimize generative AI models using LangChain, LLaMA, Hugging Face, etc. Develop RAG pipelines and integrate with LLMs for advanced AI solutions. Create, test, and optimize prompt templates across different base models. Implement guardrails for prompt security to prevent prompt injection, jailbreaks, and leaks. Build efficient backend applications using Python, Django, and related tools. Work with vector databases to enhance generative AI workflows. Collaborate on data grooming and model training across business units. Benchmark model performance and develop auto-prompting systems. Ensure adherence to minimum design standards in prompt engineering use cases. Mandatory Skills Gen AI, LLMs, RAG Pipelines LangChain, LLaMA, Hugging Face Python, TensorFlow, PyTorch, Django NLP, Machine Learning, Deep Learning Vector Database integration Preferred Skills Azure or AWS Cloud Platforms MLOps, Kubernetes GitHub, Bitbucket Experience with GPT-4 Domain exposure in Banking or Financial Services Join Wipro to be part of a company that thrives on innovation, reinvention, and digital excellence. Work on impactful GenAI projects, grow your career, and contribute to shaping the future of AI in real-world applications. We welcome applications from individuals with disabilities.

Senior Machine Learning Engineer Location: Bengaluru, India Company: Chevron Experience Required: 5 10 Years Department: AI/ML Engineering Work Mode: Hybrid / Global Operations Support About the Role Chevron is actively seeking a Senior Machine Learning Engineer to join our cutting-edge AI team. You will be responsible for designing, building, and optimizing advanced machine learning systems that power transformative applications in artificial intelligence. In this role, you will develop self-learning applications and refine AI systems using robust engineering, statistics, and software design practices. Key Responsibilities Study and transform data science prototypes into production-ready systems Design scalable and robust machine learning systems Research and implement modern ML algorithms and tools Develop ML applications based on business and technical requirements Select appropriate datasets, data pipelines, and data representation techniques Run experiments and evaluate results to fine-tune models Perform statistical analysis and ML performance optimization Train and retrain models as new data becomes available Extend and customize existing ML libraries and frameworks Stay up to date with the latest ML research and trends Required Qualifications 5 10 years of proven experience as a Machine Learning Engineer or in a similar role Hands-on experience with Azure Machine Learning and MLOps Strong skills in data structures, data modeling, and software architecture Deep knowledge of math, probability, statistics, and algorithm design Proficient in programming languages: Python, R Familiarity with ML frameworks and libraries such as Keras, PyTorch, scikit-learn Excellent analytical and problem-solving skills Strong communication and teamwork abilities Working Hours Chevron supports international teams. Work hours are scheduled to align with global collaboration: Work Days: Monday to Friday Shift Options: 8:00 AM 5:00 PM or 1:30 PM 10:30 PM IST Opportunity to work on impactful ML/AI solutions at enterprise scale Flexible work culture with global exposure Advanced tools, infrastructure, and data at your fingertips Professional growth in a forward-thinking, innovation-driven environment Equal Opportunity Statement Chevron is an equal opportunity employer and adheres to inclusive hiring practices. All qualified candidates will receive consideration without regard to race, gender, age, religion, nationality, sexual orientation, disability, or any other protected status. Chevron also participates in E-Verify as required by law in applicable jurisdictions. Apply Today

Engineer, Principal/Manager - Machine Learning, AI Location: Bangalore, Karnataka, India Company: Qualcomm India Private Limited General Summary Qualcomm is seeking an experienced and visionary Principal AI/ML Engineer to lead research, development, and optimization of AI inference systems. This role involves developing high-performance AI models, optimizing deployments across various hardware platforms, and contributing to research in model compression, quantization, and hardware-aware optimization. Education & Experience PhD with 6+ years, Master's with 7+ years, or Bachelor's with 8+ years in Engineering, CS, or related field. 20+ years of experience in AI/ML development; 5+ years in inference optimization and debugging. Key Responsibilities Model Optimization & Quantization Optimize models using quantization (INT8, INT4, mixed precision), pruning, and knowledge distillation. Implement PTQ and QAT techniques for deployment. Experience with TensorRT, ONNX Runtime, OpenVINO, TVM. AI Hardware Acceleration & Deployment Target platforms: Hexagon DSP, CUDA GPUs, TPUs, NPUs, FPGAs, Habana Gaudi, Apple Neural Engine. Use Python APIs: cuDNN, XLA, MLIR for hardware acceleration. Benchmark and debug performance across platforms. AI Research & Innovation Research on efficient AI inference: model compression, low-bit precision, sparse computing. Explore architectures like Sparse Transformers, Mixture of Experts, Flash Attention. Publish in ML conferences: NeurIPS, ICML, CVPR; contribute to open-source projects. Technical Expertise Optimization of LLMs, LMMs, LVMs for inference. Deep Learning frameworks: TensorFlow, PyTorch, JAX, ONNX. Expert in CUDA, cuPy, Numba, TensorRT, ONNX Runtime, OpenVINO. Skilled in Python for scalable AI development. Experience with ML runtime delegates: TFLite, ONNX, Qualcomm AI Stack. Debugging: Netron, TensorBoard, PyTorch Profiler, Nsight, perf, Py-Spy. Cloud inference: AWS Inferentia, Azure ML, GCP AI Platform, Habana Gaudi. Hardware-aware optimization: oneDNN, ROCm, MLIR, SparseML. Contributions to open-source and research publications are a strong plus. Leadership & Collaboration Lead a team of engineers in Python-based AI inference and optimization. Collaborate with researchers, software engineers, DevOps, and hardware vendors. Define debugging, deployment, and performance tuning best practices.

Position: Senior Data Scientist Location: Bangalore Employment Type: Full-time Experience Required: 5 to 7 years Purpose of the Position: The Senior Data Scientist will play a key role in designing, developing, and implementing machine learning models and algorithms to solve complex business problems. The role involves collaborating with data scientists, software engineers, and business stakeholders to deliver scalable, efficient machine learning solutions that drive innovation and improve business outcomes. Key Responsibilities: Model Development and Optimization: Develop, train, and optimize machine learning models to meet business objectives. Ensure models are accurate, efficient, and scalable. Data Pipeline and Infrastructure: Design and maintain robust data pipelines to support machine learning workflows. Ensure data quality and integrity throughout the data lifecycle. Deployment and Monitoring: Deploy machine learning models into production. Monitor model performance and implement improvements as needed. Collaboration and Communication: Work with cross-functional teams to understand business requirements and translate them into technical solutions. Communicate complex technical concepts to non-technical stakeholders. Research and Innovation: Stay up to date with the latest advancements in machine learning and AI. Experiment with new techniques and technologies to enhance the organization's capabilities. Essential Skills: Machine Learning Frameworks: Experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn. Programming Languages: Strong skills in Python and R. Data Processing: Experience with tools like Pandas, NumPy, and Spark. Model Deployment: Experience with Docker, Kubernetes, MLflow, and FastAPI. Databases: Strong experience in databases like Snowflake, MongoDB, and Cosmo DB. Statistical Analysis: Strong foundation in statistics and probability. Model Management: Experience establishing model management, monitoring, support, and maintenance frameworks. ML Lifecycle: Experience setting up ML lifecycle processes and governance policies, as well as providing L0, L1, and L2 support. Desired Skills: Deep Learning: Familiarity with deep learning frameworks like TensorFlow or PyTorch. Natural Language Processing (NLP): Understanding of NLP techniques and applications. Cloud Computing: Experience with cloud platforms like AWS, Azure, or Google Cloud. Big Data Technologies: Knowledge of big data technologies such as Hive, Pig, or Cassandra. Software Engineering: Proficiency in software development and version control systems like Git. Qualifications: Education: Master's degree or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, or a related field. Experience: Over 5 years of experience in machine learning, with a proven track record of developing and deploying models. Certifications: Relevant certifications in machine learning or data science are a plus. Key Qualities: Analytical Thinking: Strong analytical and problem-solving skills. Communication: Excellent verbal and written communication skills. Team Player: Ability to work effectively in a collaborative team environment. Adaptability: Flexibility to adapt to changing business needs and technologies. Innovation: A proactive approach to exploring new ideas and technologies. Apply now to join our dynamic team and lead innovation through machine learning and AI! Qualification : Master's degree or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, or a related field.

Your Impact We are seeking a passionate Data Engineer with expertise in Python development who is excited about cloud-based data engineering using AWS services. You will be an integral part of a dynamic, multi-disciplinary team, working closely with digital product professionals, data scientists, cloud engineers, and other stakeholders. As a key member of a global team working on our generative AI initiative, you will be based in one of our European offices. McKinsey s Tech Ecosystem function is responsible for developing and delivering all technology solutions for the firm s internal use, and your role will be crucial in driving the development of data solutions to support generative AI applications. You will work with a team of data engineers to develop robust data ingestion pipelines and enhance data processing capabilities that integrate data into systems used by AI applications. Your responsibilities will include writing Python code, creating tests, developing and maintaining GitHub Action CICD pipelines, and managing AWS-based infrastructure and Docker containers. Your Growth As a member of the global team working on our generative AI initiative, you will play a key role in shaping and accelerating the delivery of McKinsey's target state data platform, which will enable AI use-cases. You will be part of our cloud-first approach, transforming data platforms and analytical applications across the firm. Working closely with multidisciplinary teams, you will contribute to building cutting-edge data solutions in a fast-paced, innovative environment. McKinsey s Tech Ecosystem function is responsible for developing all technology solutions for the firm s internal needs, and you ll have the opportunity to shape how these solutions evolve. Your Qualifications and Skills 3+ years of professional experience as a Data Engineer, with a focus on cloud-based data engineering using AWS services Expertise in Python development and a strong understanding of clean code, modularity, error handling, and test automation Extensive experience with relational databases and data pipeline performance Hands-on experience with Docker and CI/CD pipelines (e.g., GitHub Actions) Strong execution focus, with the ability to work independently in complex, fast-paced environments and deliver results Demonstrable experience in solving data pipeline performance issues and diagnostics Interest in generative AI and machine learning topics Experience with Kedro framework is a plus Opinionated and confident in sharing ideas, willing to speak up at all levels Familiarity with Agile principles and product development methodologies Excellent problem-solving skills and the ability to analyze and resolve complex data engineering challenges Strong communication and collaboration skills, with the ability to work effectively in cross-functional teams