Lead AI ML Engineer

Job description

**Key Responsibilities:** - Lead design, development, and deployment of AI/ML solutions. - Build reusable models for prediction, classification, NLP, CV, and Generative AI use cases. - Define AI/ML standards, testing frameworks, and performance benchmarks. - Collaborate with MLOps teams for model deployment, monitoring, and retraining. - Mentor Data Scientists and ML Engineers. - Ensure compliance with Responsible AI, security, and data privacy requirements. **Technical Skills:** - Deep Learning (CNN, RNN, Transformers), LLMs, RAG, Generative AI. - TensorFlow, PyTorch, Hugging Face, MLflow. - Python (Expert), R, C++, CUDA. - Docker, Kubernetes, CI/CD, TensorFlow Serving/TorchServe. - AWS SageMaker, Azure ML, Google Vertex AI. - Model optimization techniques such as Quantization, Pruning, ONNX, and TensorRT. - NLP, Computer Vision, Time Series Forecasting, and AI Agent frameworks. **Preferred Skills:** - Strong leadership, stakeholder management, and communication skills. - Experience in large-scale digital transformation or government projects. - Knowledge of AI Governance and Responsible AI practices. Provide your feedback on BizChat **Education:** - B.Tech/M.Tech/M.S./Ph.D. in Computer Science, AI/ML, Data Science, or related fields. - Relevant AI/ML certifications preferred. - Research publications, patents, or open-source contributions are an advantage. **Experience:** - 710 years of AI/ML experience. - 4–5 years of experience leading AI/ML teams. - Proven experience in developing and deploying AI/ML solutions at scale.