{"id":1230740,"url":"https://alion.io/job/optum-senior-aiml-engineer","title":"Senior AI/ML Engineer","company":{"id":20903,"name":"Optum","domain":"optum.com","url":"https://alion.io/company/optum","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India","Bengaluru, India","Noida, India","Gurgaon, India","Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":43000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":29},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"DPO","optional":false},{"name":"Embeddings","optional":false},{"name":"FAISS","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Gemini","optional":false},{"name":"GraphRAG","optional":false},{"name":"GRPO","optional":false},{"name":"InfiniBand","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"LLM","optional":false},{"name":"LoRA","optional":false},{"name":"Machine Learning","optional":false},{"name":"Milvus","optional":false},{"name":"Mistral","optional":false},{"name":"NCCL","optional":false},{"name":"NLP","optional":false},{"name":"OCR","optional":false},{"name":"OpenAI","optional":false},{"name":"PPO","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"QLoRA","optional":false},{"name":"Qwen","optional":false},{"name":"RAG","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"RLAIF","optional":false},{"name":"RLHF","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"SFT","optional":false},{"name":"SQL","optional":false},{"name":"Weaviate","optional":false},{"name":"PEFT","optional":true}],"status":"live","first_seen_at":"2026-09-17T11:34:48Z","employer_posted_date":null,"last_verified_at":"2026-09-17T11:34:48Z","board_verified":false,"closed_at":null,"days_open":14,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":14},"description":"Job Description :\n\n- 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.\n\n- Deep knowledge and extensive experience with Machine/Deep Learning frameworks including transformer architectures, state space models, large language models, and agentic approaches.\n\n- Knowledge of algorithms and techniques within a computational domain with emphasis on text processing.\n\n- Architect and implement GraphRAG pipelines, including knowledge graph representation and retrieval for enhanced contextual grounding.\n\n- Design, train, and optimize semantic and dense vector embeddings for document understanding, search, and retrieval.\n\n- Develop semantic retrieval systems with advanced document segmentation and indexing strategies.\n\n- Build and scale distributed training environments using NCCL and InfiniBand for multi-GPU and multi-node training.\n\n- Apply reinforcement learning techniques (e.g., RLHF, RLAIF) to align model behavior with human preferences and domain-specific goals.\n\n- Experience with Hybrid NLP solutions that combine symbolic and machine learning approaches.\n\n- Collaborate with cross-functional teams to translate business needs into AI-driven solutions and deploy them in production environments.\n\nQualifications :\n\n- Graduate degree or equivalent experience.\n\n- PhD or Masters degree in computer science, Machine Learning, or related field.\n\n- 10+ years of experience in applied AI/ML with statistics, with a strong track record of delivering production-grade models.\n\n- Deep expertise in NLP, Fundamental machine learning, deep learning, transformer, state space-based architecture.\n\n- Azure ML and/or AWS.\n\n- Strong in Python coding, SQL and database queries, data preparation, and analysis.\n\n- Exploratory Data Analysis (EDA).\n\n- Experience with PyTorch.\n\n- LLM training and fine-tuning (e.g., GPT, LLaMA, Mistral, Qwen).\n\n- Graph-based retrieval systems (GraphRAG, knowledge graphs).\n\n- Embedding models (e.g., BGE, E5, SimCSE).\n\n- Semantic search and vector databases (e.g., FAISS, Weaviate, Milvus).\n\n- Document segmentation and preprocessing (OCR, layout parsing).\n\n- Model fusion and ensemble techniques (stacking, boosting, gating).\n\n- Optimization algorithms (Bayesian, Particle Swarm, Genetic Algorithms).\n\n- Reinforcement learning (e.g., RLHF, PPO, DPO, GRPO), Supervised Fine Tuning (SFT), LoRA, QLoRA, axolotl.\n\nEducation :\n\n- UG : Any Graduate.\nSkills\nArtificial Intelligence, Machine Learning, LLM, Deep Learning, NLP, RAG, AWS, Python, PyTorch","description_format":"text","description_chars":2618,"description_truncated":false,"requirements":{"experience_years_min":10,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Primary Care & Medical Centers","Revenue Cycle & Medical Billing","Health Data & Interoperability","Health Insurance & Benefits"],"lifecycle":[{"event":"open","at":"2026-09-25T14:00:00Z"}],"liveness":{"score":70,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.781,"p_room":0.9,"age_days":13,"expected_fill_days":24,"reasons":["seen:13","velocity","win:mid"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/optum-senior-aiml-engineer","json_url":"https://alion.io/job/optum-senior-aiml-engineer.json","meta":{"generated_at":"2026-10-01T21:02:41Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":3523,"day_limit":5000,"remaining_today":1477,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}