Top Machine Learning Engineer Jobs in Mumbai

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 and implement map and location quality testing end-to-end: statistical/experimental designs, sampling plans, ML models, metrics, and data/computing tools. Serve as SME, collaborate with stakeholders and customers, present findings, and lead quality strategy and implementation for map quality evaluation.

Lead development and deployment of scalable machine learning and analytics solutions for global map-making. Design process automation, build predictive and statistical models, lead modeling teams, collaborate with researchers, developers, architects, and customers, and work with big-data pipelines and point-cloud/computer-vision methods.

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.

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.

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.

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.

The Director of Data Science will lead the development of AI systems, manage a team, and drive knowledge sharing while ensuring project alignment with business goals.

Lead design and delivery of scalable automation and AI/BI solutions for KYC operations. Build advanced Tableau dashboards, integrate ML/AI workflows, validate outputs, ensure governance and compliance, mentor technical teams, and collaborate with stakeholders to translate business requirements into production-ready solutions.

Lead design and delivery of scalable BI and AI-driven automation for KYC operations. Build advanced Tableau dashboards, integrate ML models, ensure output governance, collaborate with engineering and business stakeholders, and mentor technical teams.

Lead design and delivery of scalable automation and AI/ML-integrated BI solutions for KYC operations. Develop advanced Tableau dashboards, implement AI-driven workflows, ensure output validation and governance, collaborate with data engineers and stakeholders, and mentor technical teams while ensuring compliance and production reliability.

Work with business and technology teams to gather and document requirements, design future-state processes, identify automation and AI opportunities (RPA/LLMs/VLMs), own UAT, and support delivery and stakeholder adoption across trading lifecycle transformation projects.

Intermediate KYC analyst responsible for AML monitoring, KYC reviews, regulatory reporting, remediation project management, root cause analysis, and stakeholder engagement. Ensures compliance with Citi standards and local regulations, provides QA and commentary on returns, participates in regional initiatives, and drives process improvements using CitiKYC tools and data analysis.

Support KYC program operations by creating and validating KYC records, sourcing internal/external data, keeping workflow tools current, meeting SLA targets, escalating high-risk findings, and assisting compliance reporting and projects.

Entry-level KYC Operations Analyst assisting AML monitoring, KYC record creation and validation, interacting with relationship and compliance teams, maintaining workflow tools, meeting daily targets, escalating high-risk cases, and supporting reporting and departmental projects.

Lead a team of data scientists in developing and deploying machine learning models, ensuring code quality, documentation, and smooth industrialization of projects.

Lead design, development, and deployment of production ML systems for HD mapping, ADAS and IVI. Own end-to-end ML architecture, data ingestion, training, inference pipelines, MLOps (CI/CD, versioning, monitoring), and integrate outputs into map compilation. Drive models in computer vision, NLP, generative/agentic AI, and ensure scalable, reliable in-cloud or in-vehicle deployments while mentoring teams and enforcing engineering best practices.

Lead strategic client accounts, managing relationships with senior executives to drive sales growth and tailored solutions, especially in financial services.

The role focuses on developing analytical data science products, implementing algorithms for insights, and expertise in deep learning frameworks.

Design, develop, and deploy chatbots and voice bots using Dialogflow CX and Google CCAI. Build Python backends, integrate with databases and APIs, apply NLP/LLM/TTS/STT/SSML techniques, debug distributed systems, and collaborate with cross-functional teams to deliver scalable conversational AI solutions.

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.

Independently review and analyze trade surveillance reports across asset classes, investigate and resolve alerts with stakeholders, document findings, support tuning and calibration of surveillance models, assist control design and deployment, prepare management reporting, support regulatory inquiries and audits, and collaborate with IT/vendors on tool development and testing.

Own the product lifecycle for enterprise AI-enabled solutions: define strategy and roadmap, lead discovery, define requirements and KPIs, prioritize backlog, coordinate engineering/data/design/delivery, ensure secure and responsible AI deployments, and measure adoption and business impact.

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.

Consult with CPG/FMCG clients on Revenue Growth Management analytics programs, focusing on pricing strategies, promotion analysis, and optimizing revenue growth while leading engagements across diverse global markets.