Walk in drive-AI ML Engineer-27-JUNE (Chennai)

Senior AI/ML Developer Years of experience: 5+ years (with minimum 4 years of relevant experience) Skill:Python, Fast API,Gen AI,Agentic AI,Langchain and LangGraph (Must have) Tensorflow,SQL, MLops,AWS,Azure (Valuable to have) Role & responsibilities - Architect and design scalable, production-grade AI/ML systems and data pipelines. - Collaborate with stakeholders to identify and scope use cases for machine learning, deep learning, NLP, and computer vision. - Lead the selection and implementation of AI/ML frameworks, platforms, and tools (e.g., TensorFlow, PyTorch, Scikit-learn). - Guide teams in model development, training, evaluation, deployment, and monitoring in production environments. - Define MLOps strategy for CI/CD, model versioning, retraining, and governance. - Ensure solutions are optimized for performance, scalability, security, and compliance. - Work closely with data engineers to ensure robust data pipelines, feature stores, and data quality standards. - Serve as an AI thought leader within the organization, mentoring engineers and promoting best practices. - Evaluate new AI technologies and platforms to drive innovation and maintain competitive advantage. - Contribute to documentation, standards, and architecture governance. Senior AI/ML Developer Years of experience: 5+ years (with minimum 4 years of relevant experience) Skill:Python, Fast API,Gen AI,Agentic AI,Langchain and LangGraph (Must have) Tensorflow,SQL, MLops,AWS,Azure (Valuable to have) Role & responsibilities - Architect and design scalable, production-grade AI/ML systems and data pipelines. - Collaborate with stakeholders to identify and scope use cases for machine learning, deep learning, NLP, and computer vision. - Lead the selection and implementation of AI/ML frameworks, platforms, and tools (e.g., TensorFlow, PyTorch, Scikit-learn). - Guide teams in model development, training, evaluation, deployment, and monitoring in production environments. - Define MLOps strategy for CI/CD, model versioning, retraining, and governance. - Ensure solutions are optimized for performance, scalability, security, and compliance. - Work closely with data engineers to ensure robust data pipelines, feature stores, and data quality standards. - Serve as an AI thought leader within the organization, mentoring engineers and promoting best practices. - Evaluate new AI technologies and platforms to drive innovation and maintain competitive advantage. - Contribute to documentation, standards, and architecture governance.