Top Machine Learning Jobs in India

Drive regional sales growth for AI-powered credit underwriting and risk assessment solutions across banks, NBFCs, fintechs, and financial institutions. Responsibilities include lead generation, stakeholder relationship management, end-to-end sales cycle ownership, proposal development, negotiation, deal closure, sales target achievement, pipeline reporting, and collaboration with product, marketing, technology, and customer success teams.

Develops full-stack AI and machine learning applications using web technologies, statistical modeling, deep learning, databases, cloud platforms, and APIs. Designs algorithms, translates technical specifications into code, performs testing and debugging, documents solutions, and improves product and system performance. Works independently on complex initiatives, collaborates with stakeholders, mentors colleagues, and may manage projects or review others’ work.

Lead and support data analytics and automation initiatives for Global Markets Business Controls. Build, maintain and deliver data preprocessing, analysis, aggregation and visual reports. Identify process weaknesses, design workflows, drive operational improvements, and translate technical findings to business stakeholders while managing multiple scheduled and ad-hoc tasks.

Lead design and implementation of high-throughput risk calculation engines and scalable risk workflows. Architect cloud-first, AI-enabled, multi-region high-availability platforms; provide hands-on technical leadership, mentor engineers, and collaborate with quantitative teams and product managers to modernize legacy systems and deliver resilient risk metrics and workflows.

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 data analysis and engineering to enable data-driven decisions: investigate data quality and lineage, build automated pipelines, apply advanced analytics and ML, design interactive dashboards and reports, translate insights into business recommendations, and support governance and controls while coaching or leading team members.

Design, develop, and optimize ETL pipelines and repositories for large-scale medical imaging (CT, MRI). Integrate with PACS/XNAT, extract and standardize DICOM/HL7/FHIR metadata, implement automated labeling/segmentation, and optimize AWS storage and retrieval for high-performance clinical applications.

Lead product analytics for a mobile esports platform: design and analyze A/B experiments, surface user-level behavioral insights, influence product roadmap with opportunity sizing, build models for propensity/LTV/churn, and apply agentic AI and BI tooling to turn data into executive recommendations.

Develops data-driven opportunities and translates business needs into research questions. Performs data preparation, quality control, statistical analysis, mathematical modeling, machine learning, and forecasting. Communicates findings to business partners, supports strategic decisions, and trains stakeholders to interpret results. Collaborates with Data Science Engineers across the data pipeline, evaluates solution validity, and applies advances in statistics, optimization, NLP, AI, and analytical modeling.

Designs, builds, deploys, and scales production-grade AI solutions, focusing on Generative AI, Agentic AI, LLMs, RAG, intelligent assistants, automated workflows, and AI pipelines. Translates business needs into measurable AI applications across search, recommendations, document processing, language processing, and autonomous agents. Collaborates with technical and nontechnical stakeholders, identifies new AI opportunities, and promotes emerging technologies and organizational AI maturity.

Design, train, fine-tune, and evaluate foundation models and vision-language models for multi-sensor satellite imagery. Develop detection, segmentation, change detection, retrieval, captioning, and visual question-answering systems. Build scalable geospatial data pipelines, conduct rigorous experiments, publish research, and collaborate with engineering, MLOps, product, and domain teams to transition prototypes into production.

Own core backend computation services that transform financial and operational data into correct, reproducible, traceable results. Design configuration-driven component libraries and runtimes, set-based warehouse computations, tenant-level guardrails, feature controls, audit logging, and data lineage. Build isolated, multi-cloud-ready customer-hosted deployments and integrate them with enterprise environments. Work directly with customer engineering and finance teams, establish backend architecture patterns, review designs, mentor engineers, and collaborate with data, AI, and product teams.

Leads the design and implementation of automated testing frameworks for web, mobile, API, and performance testing. Collaborates with development and QA teams on automation strategies, maintains test scripts and documentation, reviews code, analyzes defects, and supports manual testing. Mentors junior engineers and evaluates testing tools. Requires Java or Python, API testing, SQL, SDLC, Agile/Scrum, test lifecycle, version management, and test management experience. CI/CD, ML testing, performance testing, BDD, cloud, and data lake testing are preferred.

Lead end-to-end development and productionization of ML models and scalable data pipelines for personalized retail and digital banking. Research and implement algorithms (NLP, CV, recommendation, time series, etc.), collaborate with cross-functional teams, ensure regulatory compliance, communicate insights to stakeholders, mentor junior ML staff, and contribute to firm ML community.

Design, develop, experiment, and productionize NLP and machine learning models, services, and scalable data pipelines. Contribute across the full product lifecycle, implement algorithms and systems, and drive continuous learning and improvement within the AI for Operations team supporting banking operations.

Lead design and delivery of production-scale AI/ML solutions for Market Operations. Manage and mentor a team of data scientists and engineers, partner with stakeholders and AI engineering to build scalable architectures, ensure production-grade code and MLOps practices, establish model evaluation/monitoring/governance, and drive execution and documentation to deliver measurable business impact.

Lead design, prototyping, and production deployment of LLM- and GenAI-based solutions for compliance and risk. Build agentic AI, RAG/GraphRAG, MCP integrations, knowledge graphs, Python services, and partner across Compliance, Technology, and Product to operationalize AI with governance and best practices.

Design, develop, and productionize end-to-end AI/ML solutions for employee experience, HR, and operations. Perform data wrangling, analysis, modeling, documentation, R&D on novel approaches, stakeholder engagement, and coach junior team members while collaborating across the firm to deliver data-driven business impact.

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.

Lead design and delivery of conversational AI and voice solutions (Dialogflow) across platforms (Genesys, AWS Connect). Build/optimize voice bots, LLM-based capabilities (Gemini Enterprise CX), real-time streaming with LiveKit, integrate AI with backend systems, establish scalable architectures and MLOps, and lead technical teams to improve customer experiences.

Design, build, and deploy generative AI applications and traditional ML models. Implement RAG, embeddings, vector search, prompt engineering, fine-tuning, and scalable services integrating third-party AI APIs. Establish model evaluation, monitoring, CI/CD, and guardrails. Collaborate with product, data, and engineering teams to productionize ML features and ensure reliability and low-latency performance.

Build data infrastructure and reliable pipelines, analyze product usage, train traditional and LLM-based models, define product metrics, run experiments, and translate findings into product and go-to-market decisions. The role combines data science, data engineering, product analytics, machine learning, and stakeholder communication, with ownership across data modeling, evaluation, experimentation, and product insight generation.

Lead and grow an engineering team responsible for Wi-Fi optimization, device management, provisioning, lifecycle, and cloud connectivity control systems. Own the roadmap, architecture, delivery, reliability, hiring, coaching, and performance of 8–12 engineers. Drive cross-functional execution, customer escalations, standards strategy, design reviews, coding, and large-scale operational decisions across embedded, cloud, and networking systems serving tens of millions of devices.

Develop and maintain machine learning models, statistical tools, predictive analytics, segmentation, and document classification solutions for mortgage operations. Translate business needs into modeling tasks, build experiments, support data pipelines and model deployment, and monitor model performance. Apply supervised learning, clustering, NLP, and automation techniques while maintaining documentation and audit readiness. Collaborate with Product, Engineering, Analytics, and senior data science teams in a regulated financial environment.