Top Machine Learning Engineer Jobs in Mumbai

Lead enterprise AI transformation engagements through technical discovery, demonstrations, pilots, workshops, solution architecture, and adoption planning. Drive technical wins and pipeline for Microsoft 365 Copilot, Copilot Studio, Agents, and related Microsoft solutions. Translate business needs into secure, scalable architectures, remove technical blockers, support partner co-selling, maintain opportunity hygiene, and mentor engineers while influencing product and go-to-market strategy.

Research Engineer applying frontier machine learning and reinforcement learning research to production AI capabilities. Responsibilities include model design, training, evaluation, RLHF, multi-objective optimization, LLM post-training, reward modeling, auditing, and translating prototypes into reliable systems. The role also involves customer engagement, technical communication, and shaping research and product strategy.

Leads commercial performance for global and regional eCommerce markets, improving revenue, margin, EBIT, conversion, AOV, demand shaping, customer experience, and retention. Partners with market leaders to diagnose performance, recommend actions, align improvement plans, govern KPI frameworks, and ensure adoption. Leads data storytellers, establishes analytical and measurement standards, develops global playbooks, and influences senior stakeholders across a global matrix organization.

Build and productionize LLM-powered agents, workflows, and RAG systems. Apply prompt engineering, embeddings, fine-tuning, and traditional ML to automate tasks and improve products. Mentor teammates and help design scalable, production-grade AI infrastructure while staying current on LLM advances.

Lead technical support for B2B customer deployments, diagnosing issues across ML models, applications, APIs, infrastructure, networking, and deployment environments. Investigate incidents, review logs and configurations, coordinate escalations with FDE, SRE, and Engineering teams, monitor deployment health, document root causes, communicate with customer stakeholders, and develop tools and dashboards to meet support SLOs.

Leads the architecture and technical vision for scalable AI-powered applications, including LLM inference, RAG pipelines, autonomous agents, conversational interfaces, and intelligent dashboards. Designs secure cloud and hybrid platforms, establishes GenAI engineering standards, drives reusable AI frameworks, and ensures governance, privacy, compliance, and responsible AI practices. Partners with clients, product teams, designers, and executives; mentors engineers, reviews designs and code, conducts technical discovery, and translates business requirements into durable enterprise architectures.

Build and maintain mission-critical wealth management systems for SMB clients. Design data pipelines, ETL/ELT processes, data models, warehouses, analytics, and reporting solutions using AWS, Snowflake, Mage AI, and other big data tools. Collaborate with data scientists and analysts on predictive models, statistical analyses, and machine learning algorithms. Develop software with Next.js and Python while working closely with the team and clients on financial-domain challenges.

Own and improve the Command|Alert alerting platform, including rule evaluation, anomaly detection, event correlation, reliable Kafka and OpenSearch pipelines, and downstream notifications. Convert security and network telemetry into usable topologies and dependency maps, support LLM-based alert generation, resolve production issues, lead reliability improvements, deliver independent projects, and mentor engineers while shaping technical direction.

Drive adoption of Databricks Genie across a regional territory through technical strategy, executive engagement, workshops, presentations, demos, and customer-facing collateral. Partner with Account Executives, GTM, Product, Engineering, GSIs, and consulting firms. Architect governed analytics solutions spanning semantic models, warehouses, metric layers, Lakehouse, and AI ecosystems; address governance and security concerns; resolve complex technical escalations; and provide roadmap feedback.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Develop machine learning architectures, models, data pipelines, and production systems using Python, PySpark, SQL, AWS, NLP, LLMs, and Generative AI. Collaborate with engineers, analysts, delivery managers, and clients to deliver measurable business outcomes. Communicate insights, identify sales opportunities, mentor junior engineers, manage client relationships, and support project delivery.

Design, develop, and optimize secure, scalable cloud data platforms and ETL/ELT pipelines across AWS, Azure, and GCP. Write Python and SQL, implement data governance and quality controls, optimize performance and costs, and support analytics and BI layers. Contribute to architecture, pre-sales demos, proofs of concept, and client discussions. Mentor junior developers, conduct code reviews, and collaborate with architects, QA, DevOps, and business stakeholders.

Develop and improve digital products using .NET Core and related frameworks. Implement features, fix issues, collaborate with global product teams, research solutions, and follow development best practices.

PhD intern will research and prototype AI techniques for Azure SQL Database, analyze algorithms on large datasets, build scalable ML systems, collaborate with researchers and product teams, and contribute to technology transfer and publications.

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.

Designs and deploys AI, Generative AI, intelligent automation, and process intelligence solutions to automate business processes and improve operational efficiency. Identifies automation opportunities, integrates AI with enterprise systems, analyzes processes using process mining, and delivers scalable, secure solutions. Collaborates across functions to translate business needs into measurable outcomes, while potentially leading workstreams, mentoring colleagues, shaping automation roadmaps, and supporting organizational AI transformation.

Own product initiative delivery from kickoff through release, coordinating Product, Engineering, Data, and Solutions. Track dependencies, risks, blockers, scope changes, timelines, testing, handoffs, and launch readiness. Maintain accurate project status and documentation while ensuring execution remains aligned with product intent. This hands-on role requires technical fluency, cross-functional communication, strong ownership, and daily overlap with an Asia-based technology team.

Leads demand-side yield strategy across iion’s ad marketplace and owns strategy for Cognitiion, its AI-driven yield optimization platform. Diagnoses marketplace performance, directs Yield Analysts, designs experiments, defines optimization metrics, and converts findings into platform requirements. Partners with marketplace, commercial, data science, engineering, and AI leadership to improve revenue, efficiency, bidding, win rates, and traffic allocation.

Support Private Bank operating model and process excellence initiatives by analyzing data, identifying automation and AI opportunities, developing business cases, and delivering workflow, reporting, and decision-support solutions. The role coordinates business, operations, technology, and COO stakeholders; manages requirements, governance, testing, implementation, adoption, and continuous improvement while using analytics to reduce risk, improve productivity, and enhance client outcomes.

Build and operate production-grade AI data pipelines and financial knowledge services for equities content. Responsibilities include processing text, tables, documents, and multimedia; creating knowledge bases and search indexes; engineering RAG retrieval and citation systems; integrating LLMs and NLP models; managing orchestration, APIs, quality, cost, observability, reliability, and scalable production operations.

Drive full-cycle sales for complex, high-value AI research workspace opportunities. Originate and close new business, support strategic renewals, expand stakeholder relationships, lead value-based workshops, and translate AI and research analytics capabilities into measurable customer outcomes. Engage senior decision-makers across enterprise, government, academic, and research organizations while developing pipelines, territories, business cases, negotiations, and long-term account growth.

Owns the full sales cycle for complex, high-value AI research workspace opportunities, from prospecting and discovery through negotiation and closure. Builds executive stakeholder relationships, generates new business, supports strategic renewals, leads workshops, develops business cases, and communicates measurable value from AI-powered research and knowledge workflow solutions. Requires enterprise sales expertise, AI fluency, consultative selling skills, and extensive regional travel.

Build and optimize cyber threat intelligence systems, data pipelines, automated workflows, and tooling. Analyze data sources and APIs, maintain the threat intelligence platform, automate analyst processes, and support investigations through scripting and data analysis. Translate requirements into technical solutions, collaborate with cybersecurity stakeholders and development teams, communicate technical concepts, and maintain workflow documentation. The role requires cybersecurity experience and Python automation skills, with preferred knowledge of threat intelligence frameworks, distributed systems, security APIs, and machine learning libraries.

Lead and oversee global KYC Operations team to deliver AML monitoring, governance, and regulatory reporting. Drive KYC program strategy, vendor coordination, process and technology improvements, training, project delivery, and ensure compliance with policies and regulations while managing teams and stakeholder relationships.

Build and deploy end-to-end data infrastructure and customer-facing solutions for generative AI applications. Collaborate directly with technical customers and AI researchers, translate business needs into engineering solutions, rapidly experiment, and deliver scalable front-end, back-end, and infrastructure features. The role also involves influencing product direction, engineering culture, and critical projects supporting enterprise and government AI initiatives.