Principal Data Scientist - Remote / Telecommute

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Job Description:

• Lead 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.
• 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.

Qualifications:

• PhD or Master s degree in Computer Science, Machine Learning, or related field.
• 8+ years of experience in applied AIML, with a strong track record of delivering production-grade models.
• 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).
• Distributed training frameworks (NCCL, Horovod, DeepSpeed).
• High-performance networking (InfiniBand, RDMA).
• Model fusion and ensemble techniques (stacking, boosting, gating).
• Optimization algorithms (Bayesian, Particle Swarm, Genetic Algorithms).
• Symbolic AI and rule-based systems.
• Meta-learning and Mixture of Experts architectures.
• Reinforcement learning (e.g., RLHF, PPO, DPO).

Must Have:

• PhD or Master's degree in Machine Learning/Data Science.
• Multi-model agents.
• Experience with text-to-image, image-to-text, speech-to-text.
• Published papers in Machine Learning/Data Science journals.
• Medical background project.

Bonus Skills:

• Experience with healthcare data and medical coding systems (e.g., CPT, CM, PCS).
• Familiarity with regulatory and compliance frameworks in AI deployment.