AI Research Scientist

• Train, fine-tune, and optimize LLMs using PyTorch and Hugging Face
• Build synthetic data generation pipelines at scale
• Develop LLM benchmarks, automated evaluation pipelines, and LLM-as-a-Judge systems
• Experiment with supervised, semi-supervised, and unsupervised learning
• Explore Mixture-of-Experts (MoE), model ensembles, distillation, and other modern LLM techniques
• Translate research ideas into reproducible experiments and production systems
• Collaborate with Stanford researchers
• Develop benchmarks and publish research papers in conferences and journals
• Work on real-world LLM and healthcare AI problems

• B.Sc. (minimum) in CS, AI, ML, NLP, or a related field
• Thesis work in LLM/NLP strongly preferred
• Publications in LLM/NLP strongly preferred
• Strong hands-on expertise working with LLMs
• Strong Python skills
• Experience with PyTorch, Hugging Face, model training, fine-tuning, and evaluation

• Fully remote work
• Approximately 50% working-hour overlap with California office hours, typically 9 AM-1 PM Pacific Time
• Access to high-performance GPU servers, including A100 GPUs, for model training and fine-tuning
• Opportunity to collaborate with Stanford researchers
• Opportunities to develop benchmarks and publish research papers in conferences and journals
• Work directly on challenging, real-world LLM and healthcare AI problems
• Full-time employment (40 hours/week)