Top Machine Learning Jobs in Chennai

The role involves designing GenAI solutions with LLMs, optimizing RAG pipelines, developing applications, and integrating AI solutions into production systems.

Drive the Search product roadmap at Bloomreach, focusing on AI, personalization, and data-driven decisions while ensuring customer engagement and market readiness.

As an AI/ML Engineer, you will develop machine learning models, collaborate with teams, monitor performance, and improve processes for life sciences applications.

The Senior Software Engineer will develop and deploy AI/ML solutions, improve model performance, and collaborate with stakeholders to enhance customer experience.

Develop and optimize RAG pipelines, fine-tune LLM models, contribute to ML and DL architectures, and implement evaluation frameworks.

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.

The role involves leading data science initiatives, mentoring team members, deploying models, and ensuring high-quality technical solutions. Responsibilities include coding, architecture design, and client requirement translation.

The AI/ML Engineer will focus on advanced parallel computing research and software architectures for AI, HPC, and Cloud solutions to improve KLA's products.

The role involves developing and implementing Machine Learning models, managing data pipelines, and supporting Data Science teams with best practices in ML operations and methodologies.

The Senior Machine Learning Engineer will design, develop, and deploy AI systems, focusing on Generative AI and LLM integration across various business operations, ensuring high performance and scalability.

The ML Product Owner will shape the supply chain platform by developing forecasting capabilities, collaborating with teams to enhance decision-making using machine learning.

The AI/ML Engineer II will design, develop, and deploy scalable AI/ML solutions, optimize model performance, and integrate AI into products. The role requires collaboration with various teams and knowledge in deploying solutions to cloud environments.

The role involves collaborating with Data Science teams to implement and manage ML models, designing GenAI solutions, and automating ML operations, while establishing best practices in ML lifecycle management.

The AI/ML Engineer II is responsible for designing, developing, and deploying AI/ML solutions. They work closely with product management and engineering teams to translate business problems into scalable AI systems, focusing on model optimization, cloud deployment, and cross-functional collaboration.

The Staff Machine Learning Engineer will design, deploy, and maintain scalable ML solutions, collaborate with teams, and enhance productivity through tooling.

Design and develop machine learning infrastructure and models, support product teams, build scalable data services, and promote collaboration within a diverse engineering team.

Join Weave's Machine Learning Team as a Staff ML Engineer to design and develop AI infrastructure, build scalable services, and guide teams in leveraging data for application development.

Develop and optimize machine learning models, manage project priorities, and improve real-world solutions using advanced ML techniques.

Develop embedded AI/ML applications for Microchip platforms, create demos, validate designs, and provide technical support to customers. Collaborate with teams on cutting-edge AI technologies.

Design, build, and optimize ASR and speech-related ML systems, handling real-world audio for production deployment and improvements.

The role involves designing and implementing Python applications using AI techniques, working with data technologies, and collaborating with teams in an Agile environment to fulfill research delivery strategy.

The role involves mentoring product teams in data and ML best practices, conducting complex data analysis, modeling, and building AI-driven workflows to automate processes and enhance product features.

The Senior Engineer will develop and deploy machine learning models and workflows, mentor junior engineers, and collaborate with cross-functional teams to improve patient care through innovative solutions.

The role requires building and optimizing LLM-based applications using Python and libraries like PyTorch and TensorFlow, focusing on MLOps and generative AI integration.

Design, build, and operate production-grade RAG pipelines: ingestion, embedding, indexing, retrieval, reranking, and grounded answer generation. Optimize search quality, latency, cost, security, evaluation metrics, and observability while partnering across teams to deploy and continuously improve enterprise retrieval systems.