corp to corp Jobs
Position: Data Scientist (LLM)
Location:Â Minneapolis, MN (Remote)
Duration: Long Term
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)Â ecosystems.
∙       Architect and implement Graph RAG 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.
∙       Deep expertise in:
∙       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)
Bonus Skills
∙       Experience with healthcare data and medical coding systems (e.g., CPT, CM, PCS).
∙       Familiarity with regulatory and compliance frameworks in AI deployment.
To apply for this job email your details to sonali@newhireconsulting.com