Top Machine Learning Jobs in Chennai

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.

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, 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.

Analyze e-commerce, finance, growth, and operational performance to deliver actionable insights. Build forecasting and predictive models, evaluate projects and KPIs, support stakeholder decision-making, and foster a data-driven culture to improve business performance across departments.

As a Senior Impact Analyst, you will analyze sustainability challenges, design and manage interventions, and work closely with smallholder communities, emphasizing rigorous research and collaboration.

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

The AI Lead will design, develop, and implement AI solutions to enhance the SDLC stages, mentor teams, and ensure responsible AI practices.

The Staff Engineer in Machine Learning will guide teams, solve client challenges, and enhance solutions leveraging their technical expertise.

Lead technology vision and architecture for enterprise projects; design cloud-native, data-driven and Generative AI solutions; ensure scalability, security, governance, and engineering excellence; run architecture reviews, POCs, and implementations; evaluate emerging technologies; influence clients via workshops and executive engagements; mentor architects and distributed engineering teams.

Design, develop, prototype and deploy complex ML/DL and image-processing algorithms for semiconductor inspection systems. Build and train models using frameworks like TensorFlow or PyTorch, write model architectures from scratch, modify loss functions, and collaborate across teams to integrate ML solutions into products.

Lead data governance for manufacturing and supply networks: define standards, data/integration specifications, roadmaps, and release stewardship. Ensure compliance, data quality, and responsible AI adoption; drive prototyping, metrics, and continuous improvement across analytics, automation, and ML lifecycles.

The Data Operations Analyst develops custom product attribution based on client needs, utilizing tagging and machine learning; ensuring data mapping accuracy and project delivery.

Build and maintain scalable backend services for an AI legal product: fine-tune LLMs, create data processing and document/OCR pipelines, integrate LLMs, and manage infrastructure with Terraform/OpenTofu and Docker.

Lead end-to-end data analysis: transform raw data, develop reports and dashboards (PowerBI), monitor performance and quality, implement ETL and data modeling, apply predictive modeling/NLP/machine learning, and support cross-functional data-driven decisions.

Lead design and delivery of end-to-end AI/ML and Generative AI solutions, architect scalable cloud-based platforms, integrate LLM/RAG/agentic systems, implement MLOps and governance, and mentor teams while driving AI strategy with stakeholders.

One-year, full-time fellowship supporting design, delivery, and evaluation of interventions for smallholder farmers. Duties include research and analysis, pilot design, field implementation, M&E, and cross-team collaboration with heavy mentorship and rotating in-country placements.

Lead complex engineering initiatives in Credit Risk Technology, overseeing software development and driving innovation using AI and Machine Learning.

As a Customer Support Engineer, you will resolve customer technical issues, perform installations, upgrade systems, and support field services while maintaining customer relationships.

Lead design, development, and delivery of complex cloud-native systems. Drive end-to-end technical execution, set engineering standards and architecture, mentor engineers, collaborate with product/UX/architecture, troubleshoot production issues, and champion performance and system improvements.

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.

Work on machine learning research and prototypes: analyze algorithms on large datasets, design experiments, prepare and clean data for modeling, and implement scalable AI system prototypes under senior guidance.

The Sr AI Solutions Engineer will update stakeholders on solutions, productize Centific AI offerings, implement NVIDIA models, and develop AI-enabled applications.

Lead architecture and development of the core native iOS SDK and related apps. Own feature delivery from design to public release, write high-quality tested code, collaborate with R&D and ML teams, support customers to resolve issues, and manage priorities across large-scale, distributed projects.

Lead post-deployment operations and optimization of Agentic AI, LLM integrations, and Python-based analytical pipelines. Supervise a data science operations team, ensure secure high-availability production systems, manage integrations with enterprise systems (SAP, Salesforce, Postgres), and drive continuous improvement, monitoring, and adoption of analytics solutions.

Lead Flutter platform architecture to power thousands of dynamically rendered mobile apps. Design modular widget libraries, state management, native integrations, performance optimizations, CI/CD and testing frameworks. Build real-time social commerce, personalization, offline-first sync, analytics, and developer tools while mentoring teams and driving Flutter ecosystem adoption.