Top Machine Learning Engineer Jobs in Mumbai

Lead the development of machine learning products by driving technical direction, designing data pipelines, and collaborating with teams to innovate solutions in consumer finance.

Lead the AI/ML team to develop anomaly detection and GenAI workflows for regulatory reporting, ensuring model explainability and validation processes. Mentor a team and advocate AI usage to improve operations.

The role involves improving search relevance and tuning production search pipelines using OpenSearch/Elasticsearch, focusing on practical, production-level systems.

Lead a Mumbai AI/ML team to build anomaly-detection models and GenAI (RAG/Agent) workflows for regulatory reporting. Design human-in-the-loop validation, embed explainability in models, build review UIs, work with Model Risk Management, and evangelize AI to operations.

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 AI/ML Engineer II role involves developing AI solutions, managing product backlogs, integrating LLMs, and collaborating on automation projects while leading improvements in IT processes.

The Data Scientist role involves predictive analytics, NLP, and Deep Learning with a focus on feature engineering for structured and text data.

The ML Engineer will develop AI/ML pipelines, optimize models, build AI applications, monitor and improve model quality, and support AI operations. Responsibilities include leveraging GCP tools and collaborating on GenAI workflows.

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.

Develop and enhance AI/ML solutions to improve patient care by collaborating with cross-functional teams and deploying machine learning models in production.

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

Lead a multi-skilled product team to develop AI/ML data science products, offering technical guidance, mentoring, and fostering innovation in analytics.

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 III translates business goals into ML metrics, leads ML model development, and oversees deployment and monitoring of AI solutions, driving innovation and collaboration across teams.

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

The Architect - Machine Learning role involves designing cloud ML solutions on AWS, implementing Generative AI models, and collaborating with cross-functional teams to enhance LLM performance for user-friendly applications.

The Associate Architect will lead the development and deployment of machine learning solutions on Azure, manage the ML lifecycle, and optimize existing models while providing technical leadership to project teams.

Develop and optimize machine learning models, manage project priorities, and improve real-world solutions using advanced ML techniques.

Design and develop machine learning infrastructure and models, support product teams, build scalable data services, and promote collaboration within a diverse engineering team.

Join Weave's Machine Learning Team as a Staff ML Engineer to design and develop AI infrastructure, build scalable services, and guide teams in leveraging data for application development.

The Senior Engineer will develop and deploy machine learning models and workflows, mentor junior engineers, and collaborate with cross-functional teams to improve patient care through innovative solutions.

The Senior AI/ML Engineer at Nansen will develop AI models for blockchain data analysis, collaborating with teams to enhance platform capabilities and mentor junior engineers.