Top Machine Learning Engineer Jobs in Mumbai

Senior GIS Data Engineer responsible for developing and maintaining geospatial datasets and data pipelines. Build, run, and optimize ETL workflows (batch to flow), transform and integrate spatial data using FME/ArcGIS/Python/SQL, ensure data quality, provide GIS consultancy, and collaborate cross-functionally to deliver scalable mapping solutions and improve processes.

The role involves designing and implementing machine learning tools for data analysis, developing pipelines for various sensor datasets, and integrating applications into verification ecosystems while guiding junior engineers.

Design and implement map and location quality testing: create experimental and sampling plans, develop ML models and statistical metrics, build data/computing tools, collaborate with stakeholders, present methods and results, and lead end-to-end quality evaluation processes.

Lead the sales technology strategy and manage product lifecycle for CRM and sales automation platforms. Collaborate with various stakeholders to implement solutions, drive digital adoption, and enable data-driven decision making.

Manage and grow a team responsible for observability, monitoring, and integrations across monetization systems. Improve reliability and data quality for billing, provisioning, subscriptions, and revenue-impacting workflows; define telemetry and integration strategies; implement anomaly detection and incident management; and partner with cross-functional stakeholders to ensure reliable customer and financial workflows.

The Engineering Manager will lead AI & ML initiatives focused on data collection, overseeing technical projects and developing a high-performing team. Responsibilities include providing technical direction, mentoring staff, ensuring system reliability, and maintaining data integrity and security. The role requires expertise in NLP and data processing with an emphasis on collaborative leadership and continuous innovation.

Design, build, and productionize ML/NLP/LLM extraction systems to convert unstructured text into structured data. Own model architecture, training, deployment, monitoring, and integration with high-throughput pipelines. Improve evaluation, scalability, and reliability while collaborating with product and engineering stakeholders and contributing to team technical excellence.

Design, build, and deploy ML and generative AI solutions for marketing. Create scalable data and model pipelines, RAG/embedding workflows, agent automations, and integrate outputs into dashboards while collaborating with Marketing and Analytics.

Oneture Technologies is seeking technology professionals across various skill areas including Software Engineering, Frontend & Full Stack, Data & AI/ML, and Cloud & DevOps to help build digital solutions.

Work with the global Quantitative Research Counterparty Risk team to calibrate, monitor and automate risk models, analyze backtesting and P&L attribution, prototype risk-model techniques, build quantitative tools, produce industry trend reports, and support stress-testing for regular and event-driven reporting.

Design, develop, and deploy production-ready AI/ML solutions using generative AI, deep learning, and cloud AI services. Lead teams, make technical decisions, integrate models into scalable pipelines (cloud or on-prem), optimize performance, and collaborate with stakeholders to align solutions with business objectives.

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.

The role involves leading balance sheet management product strategy, utilizing AI and machine learning to develop data-driven tools and analytics, and overseeing product lifecycle while collaborating with senior leaders across finance and technology.

Develop, calibrate, monitor and automate counterparty risk models and analyses; attribute P&L to risk factors; prototype risk models; build quantitative tools; produce industry trend reports and support stress testing for reporting and event response.

The Deep Researcher will develop predictive signals for financial markets using quantitative analysis, focusing on fundamental knowledge and data exploration.

Lead design, development, and deployment of production-grade ML models and pipelines for HD maps and ADAS. Own end-to-end ML architecture, implement MLOps, integrate ML outputs into map workflows, mentor engineers, conduct reviews, and drive adoption of generative, agentic, computer vision and NLP techniques for scalable, production-ready systems.

Role focused on Python-based AI/ML work within KPMG India. Posting lists a B.E./B.Tech. qualification; details on specific responsibilities or experience were not provided.

Lead design, development, training, evaluation, and productionization of scalable ML/AI models using MLOps and CI/CD. Collaborate with data, product, and engineering teams, mentor engineers, enforce ML best practices, and ensure responsible, ethical AI and model monitoring in production.

Lead AI/ML engineering vision and roadmap for healthcare and life sciences. Oversee multiple client engagements, design and deploy scalable production-grade AI solutions (ML, NLP, deep learning, computer vision, LLMs), ensure regulatory readiness, responsible AI practices, and drive adoption and value realization while managing executive client relationships and expanding AI adoption.

Sell and position the FICO Platform to enterprise clients in consumer lending and retail banking. Build senior stakeholder relationships, uncover decision-management opportunities, collaborate with pre-sales and internal teams to design solutions, and drive long-term, profitable customer engagements. Manage quarterly and annual sales targets and travel up to 50% to engage customers across Southeast Asia and adjacent industries (fintech, telecom, media, entertainment).

The Senior Business Analyst will analyze and solve complex problems in the Insurance industry, lead project teams, gather requirements, and develop innovative solutions using advanced analytics and machine learning.

The Manager of Information Technology will lead digital transformation initiatives using automation, overseeing the entire lifecycle of automation projects and ensuring alignment with strategic objectives.

Build and scale a unified AI/ML data collection platform: design, develop, test, deploy, and monitor LLM-driven data pipelines, RAG/embedding workflows, model lifecycle management, observability, and production MLOps systems to ensure reliable, maintainable, and cost-efficient ML capabilities.

Design, build, and operationalize a unified AI/ML data collection platform and production LLM workflows (RAG, embeddings, vector DBs). Lead model lifecycle management, observability, scalable inference, data quality/evaluation, distributed cloud-native architectures, and mentor engineers to deliver production-ready, cost-efficient ML systems.

Lead AI/ML initiatives as an individual contributor: design and implement ML solutions, develop and maintain code, define architecture, guide data infrastructure, and collaborate with cross-functional teams to solve business problems.