Lead AI ML Engineer

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.

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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.