Senior AI ML Engineer

Optum seeks a highly skilled Senior AI ML Engineer in Hyderabad, Telangana. This role focuses on designing, developing, and optimizing reporting solutions across Oracle HCM modules using OTBI, BI Publisher, HCM Extracts, and HDL, with strong SQL skills. The ideal candidate will have deep expertise in Large Language Models (LLMs), including training and fine-tuning both open-source (Qwen, LLaMA, Mistral) and closed-source (OpenAI, Gemini, Anthropic) models. Responsibilities include architecting GraphRAG pipelines, designing semantic and dense vector embeddings, developing semantic retrieval systems, building distributed training environments, and applying reinforcement learning techniques like RLHF. Collaboration with cross-functional teams to translate business needs into production-ready AI solutions is crucial.

Primary Responsibilities:

• Develop end-to-end training and fine-tuning of Large Language Models (LLMs), including both open-source (e.g., Qwen, LLaMA, Mistral) and closed-source (e.g., OpenAI, Gemini, Anthropic) ecosystems.
• Possess deep knowledge and extensive experience with Machine/Deep Learning frameworks, including transformer architectures, state space models, large language models, and agentic approaches.
• Demonstrate knowledge of algorithms and techniques within a computational domain, with an emphasis on text processing.
• 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.
• Comply with employment contract terms, company policies, and directives.

Required Qualifications:

• PhD or Master's degree in Computer Science, Machine Learning, or a related field.
• 10+ years of experience in applied AI/ML with statistics, with a strong track record of delivering production-grade models.
• Experience with Azure ML and/or AWS.
• Experience with Exploratory Data Analysis (EDA).
• Experience with PyTorch.
• Experience with LLM training and fine-tuning (e.g., GPT, LLaMA, Mistral, Qwen).
• Experience with Graph-based retrieval systems (GraphRAG, knowledge graphs).
• Experience with Embedding models (e.g., BGE, E5, SimCSE).
• Experience with Semantic search and vector databases (e.g., FAISS, Weaviate, Milvus).
• Experience with Document segmentation and preprocessing (OCR, layout parsing).
• Experience with Model fusion and ensemble techniques (stacking, boosting, gating).
• Experience with Optimization algorithms (Bayesian, Particle Swarm, Genetic Algorithms).
• Experience with Reinforcement learning (e.g., RLHF, PPO, DPO, GRPO), Supervised Fine Tuning (SFT), LoRA, QLoRA, axolotl.
• Experience with Prompt optimization frameworks (AutoPrompt, GreaterPrompt, DSPy), GEPA.
• Deep expertise in: NLP, Fundamental machine learning, deep learning, transformers, state space-based architectures.
• Proven solid Python coding, SQL and database queries, data preparation, and analysis skills.

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