Top Machine Learning Engineer Jobs in Mumbai

The GIS Analyst - GeoAI leads Remote Sensing and GeoAI projects, conducting image analysis and developing ML models for geospatial data, ensuring technical excellence.

The AI / ML Engineer develops production-ready AI applications using cloud and on-prem environments, specializing in generative models and large language models, while leading and mentoring teams to ensure project alignment and quality.

The Customer Success Business Partner at Lyric drives customer adoption and retention for strategic accounts, leveraging expertise in AI and supply chain operations.

WorldQuant seeks a Quantitative Researcher to develop predictive models for financial markets, emphasizing creativity and a strong quantitative background.

Lead AI initiatives, craft product vision, manage lifecycle, utilize data for decisions, and foster collaboration across teams.

Lead key client accounts for FICO, focusing on strategic partnerships, complex deal structuring, and driving business growth through tailored solutions.

This role involves overseeing multi-program delivery in Analytics, Data Science, and AI, managing teams, fostering client relations, and ensuring governance and operational excellence.

Drive the Search product roadmap at Bloomreach, focusing on AI, personalization, and data-driven decisions while ensuring customer engagement and market readiness.

The Senior Software Engineer will lead the design and development of AI-driven solutions, mentor junior engineers, and optimize AI/ML models for various applications.

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.

The role involves leading data science initiatives, mentoring team members, deploying models, and ensuring high-quality technical solutions. Responsibilities include coding, architecture design, and client requirement translation.

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 Machine Learning Engineer develops and optimizes workflows, implements advanced AI models and tools, and collaborates on data pipelines. Responsibilities include fine-tuning models and optimizing deployments for performance and cost.

The Senior Machine Learning Engineer will develop and optimize workflows, implement advanced RAG capabilities, build data pipelines, and fine-tune models while collaborating closely with Data Engineers.

The Technical Architect - Machine Learning designs multi-layered AI solutions, defines technical roadmaps, leads model evaluation, and ensures architectural alignment in AI services and governance.

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.

The AI Lead will design, develop, and implement AI solutions to enhance the SDLC stages, mentor teams, and ensure responsible AI practices.

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

Design, build, and optimize ASR and speech-related ML systems, handling real-world audio for production deployment and improvements.

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

The role involves mentoring product teams in data and ML best practices, conducting complex data analysis, modeling, and building AI-driven workflows to automate processes and enhance product features.

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.

As a Product Manager, you will drive product strategy, delivery, and feature prioritization for Enterprise Data initiatives, ensuring alignment between customer needs and business goals.

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