Key Responsibilities
• Deep knowledge and extensive experience with Machine/Deep Learning frameworks including transformer architectures, state space models, large language models, and agentic approaches
• Lead end-to-end development and implementation of Large Language Model (LLM) solutions across both open-source (e.g., Qwen, LLaMA, Mistral) and closed-source (e.g., OpenAI, Gemini, Anthropic) ecosystems.
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• Knowledge of algorithms and techniques within a computational domain with emphasis on text processing
• Demonstrated publication record in AI domain especially relating to text extraction and summarization
• Architect and implement GraphRAG pipelines, including knowledge graph representation and retrieval for enhanced contextual grounding.
• Design, train, and optimize semantic and dense vector embeddings for document understanding, search, and retrieval.
• Develop semantic retrieval systems with advanced document segmentation and indexing strategies.
• Build and scale distributed training environments using NCCL and InfiniBand for multi-GPU and multi-node training.




• Apply reinforcement learning techniques (e.g., RLHF, RLAIF) to align model behavior with human preferences and domain-specific goals.
• Experience with Hybrid NLP solutions that combine symbolic and machine learning approaches
• Collaborate with cross-functional teams to translate business needs into AI-driven solutions and deploy them in production environments.
Required Qualifications

Master’s degree in computer science, Machine Learning, or related field.
11-15+ years of experience in applied AI/ML with statistics, with a solid track record of delivering production-grade models.
Deep expertise in: NLP, Fundamental machine learning, deep learning, transformer, state space-based architecture
Azure ML and/or AWS
Strong in Python coding, SQL and database queries, data preparation, and analysis
Exploratory Data Analysis (EDA)
Experience with PyTorch
Fine-tuning (e.g., GPT, LLaMA, Mistral, Qwen)
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📌 Principal Data Scientist (Bengaluru)
🏢 Optum India
📍 Bengaluru