Top Machine Learning Engineer Jobs in Mumbai

Lead innovation and analytics in research, marketing, and sales; develop and deploy machine learning models and AI technologies while managing large data sets.

The role involves advising clients on data privacy compliance, developing privacy programs, conducting assessments, and ensuring ethical data handling practices.

The VP Business Execution drives strategy defining data/reporting initiatives, leveraging AI and ML for workflow optimization, and productively collaborating with stakeholders.

The Data Scientist will lead generative AI solution development, optimize multi-agent systems, and manage advanced AI deployments while collaborating with stakeholders and mentoring team members.

Conduct assessments in sales, marketing, and supply chain; analyze data to identify trends and solutions; collaborate globally to drive revenue and innovate solutions.

Manage client relationships, develop technology solutions, oversee project delivery, and lead a cross-functional team. Focus on business development and talent retention.

Design and maintain ETL pipelines, collaborate with stakeholders, perform data analysis, ensure data quality, and implement data governance.

The role involves driving national revenue growth in enterprise sales, managing complex engagements, and building relationships with senior executives in the manufacturing sector.

The Engagement Manager will oversee top-tier client relationships, driving the utilization of BioCatch solutions and collaborating on problem-solving and strategic planning.

The Pre-Sales Consultant engages with clients to identify needs, deliver demos, and design solutions for fraud prevention in financial services.

The Hyperscalers and Commercial Lead will develop technology-driven business strategies, drive customer adoption, and manage end-to-end sales processes while working closely with cross-functional teams.

The Lead Machine Learning Engineer designs and builds ML systems for data processing, utilizing NLP, LLMs, and cloud services to innovate AI solutions and lead cross-functional teams.

The Machine Learning Operations Engineer will develop and maintain AI systems, focusing on production-grade ML infrastructure, including APIs and CI/CD pipelines, while ensuring the reliability of deployed ML services.

The role involves diagnosing and fixing issues in image classification and detection pipelines, utilizing real-world Computer Vision systems, and ensuring production-grade 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.

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

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

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

The role involves leading product strategy and development for balance sheet management solutions using AI and analytics, collaborating with senior stakeholders, and mentoring teams in product management best practices.

Lead design, development, and deployment of Generative AI and LLM solutions across cloud environments. Engage clients, build POCs/POVs, translate business needs into data problems, develop and validate models, and operationalize models with MLOps and DevOps practices while ensuring data governance, security, and domain-aligned solutions.

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

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

Design and productionize ML models for search relevance and personalization. Collaborate on ML services with backend teams under performance constraints.

The role involves leading AI and ML strategies, integrating advanced capabilities into products, and optimizing data science models, emphasizing innovation and reliability.

Manage and develop a team of product designers, set goals, optimise processes, advocate for design resources, and contribute to design strategy.