Lead Data Scientist (LLMs, Deep Learning & RAG)

About the Role

We are seeking a highly experienced AI Scientist with strong expertise in Deep Learning, Computer Vision, Natural Language Processing (NLP), and Generative AI to design and build next-generation AI solutions for enterprise applications.

The ideal candidate will have extensive experience developing, fine-tuning, and deploying advanced machine learning and deep learning models while working across NLP, Computer Vision, LLMs, AI Agents, and GenAI workflows. This role requires hands-on technical expertise combined with the ability to collaborate with cross-functional teams and mentor junior engineers.

Immediate Joiners or Candidates with Notice Period up to 15 Days Preferred

Key Responsibilities

• Design, develop, train, fine-tune, and optimize machine learning and deep learning models.
• Build enterprise AI solutions across NLP, Computer Vision, and Generative AI domains.
• Develop and deploy AI agents using frameworks such as LangGraph and related orchestration tools.
• Design and optimize prompt engineering workflows for LLM-powered applications.
• Build and enhance Retrieval-Augmented Generation (RAG) pipelines and agentic AI workflows.
• Work with large-scale image, video, and text datasets for model training and evaluation.
• Implement MLOps best practices including model versioning, CI/CD pipelines, monitoring, and automated deployment.
• Collaborate with engineering, platform, and business teams to deliver production-ready AI solutions.
• Mentor junior data scientists and contribute to AI best practices across the organization.

Required Skills & Experience

• 7–10 years of overall IT experience with at least 7 years of hands-on Data Science experience.
• Strong expertise in Python and modern AI/ML development practices.
• Hands-on experience with TensorFlow and/or PyTorch.
• Strong understanding of Deep Learning architectures including Transformers, RNNs, Transfer Learning, and Vision Transformers (ViT).
• Experience fine-tuning pre-trained models and building custom AI solutions.
• Strong experience in NLP and Large Language Models (LLMs).
• Hands-on experience building AI Agents using LangGraph or similar frameworks.
• Experience implementing RAG pipelines and Agentic AI workflows.
• Experience handling large-scale image, video, and text datasets.
• Strong understanding of AI security, governance, and enterprise deployment requirements.
• Experience with Databricks, Azure, and MLOps practices.

Preferred Skills

• Computer Vision model development and deployment.
• CNN-based architectures, object detection, image classification, and image segmentation.
• Reinforcement Learning.
• Experience working in Linux/Unix environments.
• Experience mentoring data scientists and machine learning engineers.