Walk In Drive Ai Ml Engin June Chennai (India)

Senior AI/ML Developer Years of experience: 5+ years (with minimum 4 years of relevant experience) Skill:Python, Quick 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 current 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, Quick 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 current AI technologies and platforms to drive innovation and maintain competitive advantage. Contribute to documentation, standards, and architecture governance.