Top Machine Learning Engineer Jobs in Mumbai

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.

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

Design and build machine learning systems for Coinbase, responsibly use generative AI tools and copilots, apply human-in-the-loop practices, and deliver measurable efficiency, cost, and quality improvements while collaborating in a remote-first environment with periodic in-person surges.

As a Forward Deployed Engineer, you'll provide technical expertise, help clients deploy Qdrant, and lead architectural reviews for scalable search solutions.

Lead development of production-ready AI/ML solutions (especially computer vision) using GenAI and cloud/on-prem pipelines; conduct research, publish, mentor, collaborate with delivery and Responsible AI teams, and apply multimodal, speech, and agentic AI techniques to enterprise problems.

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).

Design, build, and productionize AI/ML applications using LLMs and generative AI. Deploy models to cloud or on-prem pipelines, optimize neural networks, integrate AI with data systems, validate solutions, and mentor junior team members while aligning solutions to business needs.

Designs and implements production-ready AI applications using Generative AI and cloud AI services. Leads teams as an SME, makes cross-team technical decisions, deploys models (LLMs, deep learning) in cloud/on-prem pipelines, and continuously improves model performance and data workflows.

Designs and implements production-ready AI applications using generative AI and cloud/on-prem pipelines. Integrates GenAI models, deep learning frameworks, chatbots and image-processing solutions. Acts as SME, leads and mentors team, collaborates with cross-functional groups, and ensures project alignment and delivery.

Lead research and engineering for Industrial Digital Twins, simulation, robotics, and industrial AI. Design and implement production-ready AI/ML solutions (including computer vision and GenAI), collaborate with partners, mentor staff, run PoCs, publish research, and guide technical roadmaps for manufacturing and autonomous systems.

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.

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.

Develop, train, evaluate, and optimize ML solutions and data pipelines; translate business requirements into production-ready ML code; perform feature engineering, model selection, and evaluation; document work, participate in code reviews, and support testing and data issue resolution.

Early-career role analyzing PB-scale on-chain, transactional and customer data. Perform data engineering, ETL, querying, build visualizations and ML models, translate insights for teams, manage reporting environment, secure confidential data, and troubleshoot reports/databases.

Lead design and management of search and content recommendation services and models. Build personalized recommender systems using ML/AI, define success metrics with product and business teams, drive core module development, and translate PB-scale data insights into measurable product impact.

Design, develop, and maintain high-performance, secure Java backend services and APIs. Ensure reliability, scalability, and cost-efficiency across microservices, databases, messaging systems, and capacity planning. Troubleshoot, profile, benchmark, and optimize systems (including ML applications) and collaborate with Kazakhstan stakeholders.

Design, back-test and implement pricing, risk management, and agency trading strategies; collaborate with developers to integrate models into the trading platform; participate in product ideation, modeling, parameter tuning, and risk evaluation.

Design, develop, and manage large-scale search and content recommendation systems. Apply ML-based personalization to improve content matching and distribution. Lead core recommendation module development, define success metrics, and collaborate with content, product, and business teams to drive AI product upgrades and better user and business outcomes.

Design, build, and manage large-scale search and content recommendation systems using machine learning and personalization techniques. Collaborate with content, product, and business teams to define success metrics, drive AI product improvements, and maximize content value and user impact.

Early-career Performance Engineer in the Binance Accelerator Program. Perform hands-on performance testing and tuning, design AI-powered test strategies using LLMs and ML, build AI-driven anomaly detection and bottleneck analysis tools, research new AI technologies, and improve reliability of large-scale distributed systems.

Design, build, and deploy conversational AI/chatbot solutions on the Kore.AI platform. Create intents, entities, dialog flows, integrate backend systems and REST APIs, and develop responsive user interfaces with ReactJS while collaborating with UI/UX designers.

Lead an RPA team to design, develop, test, deploy, and maintain scalable automation bots (UiPath/AA/Blue Prism). Collaborate with stakeholders to assess processes, manage projects, mentor developers, troubleshoot bots, and report progress to senior management.

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.

Design, implement, and evaluate mathematical, econometric, and machine learning models for Nielsen's analytics platforms. Build scalable web-based analytical solutions in partnership with software engineers, create visualizations, document methodologies, and present results internally and externally.

Design and deliver end-to-end GenAI and ML solutions on AWS: build SageMaker pipelines, fine-tune LLMs (Llama2), implement RAG with vector stores (OpenSearch/Elasticsearch), develop LangChain-based LLM apps, perform prompt engineering, model evaluation and optimization, and collaborate with cross-functional teams to integrate models into production.