Top Machine Learning Engineer Jobs in Mumbai

Lead the architecture and development of scalable, secure, observable AI infrastructure, distributed microservices, real-time data pipelines, and agentic systems for intelligent networking. Drive technical vision, software delivery, system reliability, and operational excellence while mentoring engineers. Build production platforms processing high-volume network and operational data, integrating cloud infrastructure, machine learning, telemetry, and automation capabilities.

Seeking a Vice President to develop Machine Learning models and Gen AI use cases in Wealth Management, supporting business lines with predictive analytics and operational model management.

Lead pre-sales activities for credit underwriting and risk assessment solutions. Partner with sales, product, and technology teams to understand lender needs, design tailored functional solutions, conduct product demonstrations, prepare proposals and documentation, address client queries, and support pilots and proof-of-concepts. Act as a subject matter expert on lending workflows, risk policies, scorecards, data sources, regulations, and automation while influencing product enhancements and stakeholder decisions.

Lead and manage multiple agile engineering teams for a cloud-native SaaS platform. Own people management, strategic planning, resource and budget oversight, technical leadership, CI/CD and production quality, and stakeholder governance. Drive process improvements, risk/dependency management, and mentor team leaders while ensuring delivery of resilient, observable software with AI/ML integration.

Lead design, deployment, and management of prompt-based LLM models for NLP in financial services. Build data pipelines, MLOps tooling, and APIs; research prompt engineering and orchestration techniques; evaluate and optimize model performance; collaborate with cross-functional teams and communicate results to stakeholders.

Design, build, and operationalize a unified AI/ML data collection platform. Responsibilities include LLM/RAG pipelines, data ingestion, feature management, model lifecycle and deployment, observability, scalable distributed systems, and mentoring engineers to deliver production-ready ML solutions.

The Tech Project Manager will define and execute the vision for generative AI products, manage cross-functional teams, and oversee project lifecycles to enhance competitiveness and user experience.

Use data and advanced analytics to solve complex business problems, design and deploy scalable ML/data products on cloud platforms, collaborate with clients and cross-functional teams, and communicate actionable insights.

Advise clients on developing and implementing data governance strategies. Design policies, frameworks, and practices for data quality, privacy, metadata management, and security. Deliver governance projects, build capability with frameworks and accelerators, and promote governance awareness across stakeholders and committees.

Lead development and improvement of RES design and universe estimation using statistical methods, machine learning, and data integration. Research and prototype new methodologies, collaborate with technology and data teams, document global data science methods, support pilots and deployments, and mentor colleagues to apply advanced analytical techniques.

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

Monitor and investigate trade surveillance alerts across asset classes, escalate breaches, analyze trading patterns to identify high-risk behavior, produce management reports, support tuning and deployment of controls, work with IT/vendors on tools and testing, and assist with regulatory inquiries, inspections and surveillance projects.

Design and implement a unified orchestration layer coordinating vendor and internal LLMs and human agents. Build production-grade Python services, drive ML projects from design to delivery, ensure secure, scalable AI-enabled customer experiences, and collaborate across teams to meet security, compliance, and performance standards.

Leads consultative presales for credit and fraud risk solutions across Asia Pacific. Partners with clients and sales teams to discover challenges, develop proposals, business cases, platform demonstrations, executive presentations, and deal strategies. Serves as a subject matter expert across the risk lifecycle, payment ecosystems, authorization, authentication, lending, fraud, and collections. Supports go-to-market initiatives, innovation workshops, thought leadership, and proof-of-concept engagements, with travel of up to 50%.

Manage strategic enterprise customer relationships, serving as the primary contact for technical support, training, issue resolution, and executive engagement. Partner with sales on account health, growth, and presales activities while advocating for customer needs internally. Apply data analytics, visualization, AI tools, and automation to improve reporting, insights, troubleshooting, and customer value. Support connectivity-focused products and regularly meet clients and attend company functions.

Leads technical Developer Relations for NVIDIA AI platforms across India's financial services AI labs. Builds adoption strategies, technical demos, benchmarks, reference architectures, workshops, and performance guides. Works directly with researchers, infrastructure teams, and CTOs to profile workloads, optimize inference, debug integrations, and design secure, observable GPU deployments across cloud, data centers, Kubernetes, and hybrid environments. Translates developer feedback and workload requirements into product and engineering input.

Leads consultative solution discovery and technical presales for AspenTech APM and related software across Oil & Gas, Chemicals, Power, Mining, and Food & Beverage industries in APJ. Develops customer-specific solutions, value propositions, proposals, scopes of work, sales campaigns, and implementation roadmaps. Partners with sales, consulting, and customers to identify business challenges, demonstrate software capabilities, and drive pipeline growth. Requires strong industry, technical, analytical, communication, and consultative skills, with 50–60% regional travel.

Lead the Data Analytics function, analyze large datasets, design analytics frameworks, build Tableau/Power BI dashboards, implement AI/ML predictive solutions, ensure data governance, present insights to senior leadership, and mentor data analysts.

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.

Leads finance transformation by owning core financial processes, modernizing ERP and planning systems, deploying AI and automation, partnering with engineering and data teams, redesigning workflows, establishing controls, and driving organizational adoption. The role requires senior finance leadership, strong systems expertise, hands-on AI transformation experience, process governance, and the ability to translate between finance and technology.

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.

Design and deploy production-ready AI applications using cloud or on-premises pipelines and generative AI models. Apply LLMs, deep learning, neural networks, chatbots, and image-processing techniques. Responsibilities include researching emerging AI technologies, testing and validating solutions, optimizing AI pipelines, integrating data systems, collaborating cross-functionally, contributing to technical discussions, and mentoring junior team members.

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.

Develop production-ready AI and machine learning applications using LLMs, generative AI, cloud AI services, deep learning, NLP, chatbots, and image processing. The role involves serving as a subject matter expert, leading and mentoring teams, making technical decisions across multiple teams, deploying and improving AI systems, and ensuring model performance and application quality.

Develop and deploy machine-learning solutions and automation tools for VFX and animation pipelines. Build web interfaces, ML/MLOps services, Linux packages, and performance-critical components using Python, C++, and TypeScript. Implement testing, CI standards, observability, secure APIs, documentation, and troubleshooting. Collaborate with engineers, researchers, architects, artists, and global stakeholders while mentoring developers and delivering reliable systems under tight deadlines.