Data Scientist

Orcapod Consulting Services; Dadri, Hyderabad, Bengaluru; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

Optum is seeking a Senior AI/ML Engineer to lead end-to-end training and fine-tuning of large language models across open-source and closed ecosystems, enabling impactful health solutions. You will architect GraphRAG pipelines and develop embeddings for document understanding, search, and retrieval.

The role focuses on scalable multi-GPU training, RLHF/RLAIF alignment, and collaboration with cross-functional teams to deploy AI-driven health tech in production, complying with policies and

Qualifications

• PhD or Masters in CS/ML or related field.
• 10+ years of experience in applied AI/ML with production-grade models.
• Experience with Hybrid NLP solutions combining symbolic and ML approaches.
• Proficiency in PyTorch and Python.
• Experience with transformer architectures, LLMs, and agentic approaches.

Responsibilities

• Develop end-to-end training and fine-tuning of LLMs across open and closed ecosystems.
• Architect GraphRAG pipelines with knowledge graphs for contextual grounding.
• Design, train, and optimize semantic and dense embeddings for document understanding and retrieval.
• Develop semantic retrieval with segmentation and indexing strategies.
• Scale distributed training environments using NCCL and InfiniBand for multi-GPU/multi-node setups.
• Apply RLHF/RLAIF to align model behavior with domain goals.
• Collaborate with cross-functional teams to deploy AI solutions in production.

Skills

Python

PyTorch

NLP & DL

RL techniques

GraphRAG

Embeddings

Semantic search

Distributed training

OCR

EDA

Education

PhD in Computer Science/ML

Master's in CS/ML

Graduate degree or equivalent experience

Tools

FAISS/Weaviate/Milvus

Qwen/LLaMA/Mistral/GPT/Anthropic

NCCL/InfiniBand

Job description

Senior AI/ML Engineer(-Product Based Company & GCC Company )

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

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
• 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
• Collaborate with cross-functional teams to translate business needs into AI-driven solutions and deploy them in production environments
  
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• Graduate degree or equivalent experience
• PhD or Masters degree in computer science, Machine Learning, or related field
• 10+ years of experience in applied AI/ML with statistics, with a Solid track record of delivering production-grade models
• Experience with Hybrid NLP solutions that combine symbolic and machine learning approaches
• Experience with PyTorch
• Deep knowledge and extensive experience with Machine/Deep Learning frameworks including transformer architectures, state space models, large language models, and agentic approaches
• Knowledge of algorithms and techniques within a computational domain with emphasis on text processing
• Proven deep expertise in: NLP, Fundamental machine learning, deep learning, transformer, state space-based architecture
  Azure ML and/or AWS
• Proven solid in Python coding, SQL and database queries, data preparation, and analysis
• Exploratory Data Analysis (EDA)
• LLM training and fine-tuning (e.g., GPT, LLaMA, Mistral, Qwen)
• Graph-based retrieval systems (GraphRAG, knowledge graphs)
• Embedding models (e.g., BGE, E5, SimCSE)
• Semantic search and vector databases (e.g., FAISS, Weaviate, Milvus)
• Document segmentation and preprocessing (OCR, layout parsing)
• Model fusion and ensemble techniques (stacking, boosting, gating)
• Optimization algorithms (Bayesian, Particle Swarm, Genetic Algorithms)
• Reinforcement learning (e.g., RLHF, PPO, DPO, GRPO), Supervised Fine Tuning (SFT), LoRA, QLoRA, axolotl

Prompt optimization framework (AutoPrompt, GreaterPrompt, DSPy),