Benefits:

• Health, dental, vision, life insurance, and disability coverage (eligible from day one).

• 401(k) plan participation after 30 days.

• 11 paid holidays.

• 12 weeks of parental leave.

• Flexible “free time” PTO policy.

Key Responsibilities

• Lead end-to-end training and fine-tuning of Large Language Models (LLMs), across open-source (Qwen, LLaMA, Mistral) and closed-source (OpenAI, Gemini, Anthropic) ecosystems.

• Architect and implement GraphRAG pipelines with knowledge graph representation and retrieval.

• Design, train, and optimize semantic/dense vector embeddings for document understanding, search, and retrieval.

• Build semantic retrieval systems with advanced document segmentation and indexing.

• Scale distributed training environments with NCCL and InfiniBand for multi-GPU and multi-node setups.

• Apply reinforcement learning techniques (RLHF, RLAIF) for model alignment with human preferences.

• Collaborate cross-functionally to deliver AI-driven solutions for enterprise deployment.

Preferred Qualifications

• PhD or Master’s in Computer Science, Machine Learning, or related field.

• 8+ years of experience in applied AI/ML with production-grade deployments.

• Deep expertise in:

  • LLM training and fine-tuning (GPT, LLaMA, Mistral, Qwen).

  • Graph-based retrieval systems (GraphRAG, knowledge graphs).

  • Embedding models (BGE, E5, SimCSE).

  • Semantic search & vector databases (FAISS, Weaviate, Milvus).

  • Document segmentation/preprocessing (OCR, layout parsing).

  • Distributed training frameworks (NCCL, Horovod, DeepSpeed).

  • High-performance networking (InfiniBand, RDMA).

  • Model fusion/ensembles (stacking, boosting, gating).

  • Optimization algorithms (Bayesian, Particle Swarm, Genetic).

  • Symbolic AI, meta-learning, Mixture of Experts.

  • Reinforcement learning (RLHF, PPO, DPO).

Bonus Skills

• Experience with healthcare data and medical coding (CPT, CM, PCS).

• Familiarity with regulatory/compliance frameworks for AI deployment.

• Open-source AI contributions, published research, or experience taking research from POC to production.

Additional Information

• No sponsorship is offered at this time.

• Equal employment opportunity employer—no discrimination based on protected categories.

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