Top Machine Learning Jobs in Delhi

The Staff Engineer in Machine Learning will guide teams, solve client challenges, and enhance solutions leveraging their technical expertise.

As a Customer Support Engineer, you will resolve customer technical issues, perform installations, upgrade systems, and support field services while maintaining customer relationships.

Design and implement AI models, operationalize ML models, develop CI/CD pipelines for ML workflows, and provide technical guidance while ensuring data security compliance.

The AI/ML Consultant will design and develop AI solutions for sustainability, collaborating with teams to deliver scalable models and proof of concepts while engaging with clients for successful implementation.

The Senior Product Manager will drive AI-led innovation, define AI product strategy, ensure compliance with responsible AI principles, and collaborate across teams to deliver impactful AI features.

The Senior Data Analytics Engineer at MariaDB designs and builds data pipelines, writes SQL queries, develops internal tools, and translates data into actionable insights. They will collaborate closely with stakeholders and leverage AI tools to enhance analytics workflows.

As an AI/ML Engineer, design, develop, and deploy machine learning models and AI solutions for fintech, ensuring integration with cloud platforms and robust data pipelines.

The role involves designing, building, and scaling ML/RL systems that enhance customer experience while ensuring reliability and efficiency in production. Responsibilities include model optimization, deployment, and monitoring for performance improvements.

Responsible for the end-to-end design, development, and deployment of Machine Learning models, collaborating with teams, and managing deployment lifecycles.

Develop and scale data management systems for AutoML and forecasting platforms, ensuring data reliability and implementing SLAs across pipelines.

The role involves designing and deploying machine learning models, ensuring model performance, and optimizing ML infrastructure on GCP, collaborating closely with data engineers and scientists.

Design, implement, and maintain machine learning systems. Collaborate with data experts and transform business problems into data problems through statistical modeling and analysis.

Lead the design and deployment of AI/ML solutions focused on sustainability, mentor teams, engage clients, and ensure adherence to responsible AI principles.

The Director of AI/ML will lead the creation of a new Agentic Delivery Center in India, transforming client needs into scalable AI/ML solutions while ensuring project success and value delivery. Responsibilities include collaborating with leadership, defining architectural standards, and mentoring teams._

Design, develop, and implement ML models for search and recommendation systems. Collaborate with data engineers and scientists to integrate, enhance and scale ML solutions for personalization in various sectors.

Lead AI/ML projects, design scalable architectures, translate business needs into technical solutions, and ensure best practices in implementation.

Design, build, and productionize scalable AI/ML pipelines and models (including LLMs and Generative AI). Deploy and optimize models across cloud and edge, implement MLOps (CI/CD, versioning, monitoring), and collaborate with data scientists and engineering teams to deliver reliable, low-latency AI solutions.

The role involves designing and optimizing large-scale ML data pipelines, ensuring high-throughput data ingestion and processing, collaborating with teams on data workflows, and architecting GPU-based environments.

The role involves developing and implementing Machine Learning models, managing data pipelines, and supporting Data Science teams with best practices in ML operations and methodologies.

The Senior Machine Learning Engineer will design, develop, and deploy AI systems, focusing on Generative AI and LLM integration across various business operations, ensuring high performance and scalability.

The ML Product Owner will shape the supply chain platform by developing forecasting capabilities, collaborating with teams to enhance decision-making using machine learning.

The role involves collaborating with Data Science teams to implement and manage ML models, designing GenAI solutions, and automating ML operations, while establishing best practices in ML lifecycle management.

The AI/ML Engineer II is responsible for designing, developing, and deploying AI/ML solutions. They work closely with product management and engineering teams to translate business problems into scalable AI systems, focusing on model optimization, cloud deployment, and cross-functional collaboration.

The AI/ML Engineer II will design, develop, and deploy scalable AI/ML solutions, optimize model performance, and integrate AI into products. The role requires collaboration with various teams and knowledge in deploying solutions to cloud environments.

The Staff Machine Learning Engineer will design, deploy, and maintain scalable ML solutions, collaborate with teams, and enhance productivity through tooling.