Founding AI/Machine Learning Engineer
Core
Architect and execute post-training pipelines (SFT, RLHF, RLAIF) for large language models to ensure clinical correctness and safety in healthcare applications.
Role type
Founding AI/Machine Learning Engineer (Post-Training & Alignment)
Builds
Production-ready alignment pipelines and evaluation frameworks for medical LLMs
Domain
Healthcare + Large Language Models (LLMs)
Deliverable
production ML models
Required skills
Post-training expertise (SFT, RLHF, RLAIF, Reward Modeling, Knowledge Distillation), Transformer architecture design, distributed training on GPU clusters, Python, PyTorch, modern open-source LLM stacks (HuggingFace, Vertex, Vercel)
Preferred skills
Published research in top-tier ML/AI conferences, experience at top research labs (FAIR, DeepMind, OpenAI, etc.), multimodal health data handling, entrepreneurial product building
Technologies
PyTorch, HuggingFace, Vertex AI, Vercel, GPU clusters
Responsibilities
Design and execute alignment pipelines bridging exam-passing models to clinically useful systems, leverage proprietary medical datasets for fine-tuning, research and implement novel post-training techniques, build rigorous evaluation frameworks to detect hallucinations and ensure safety, collaborate with co-founders on research roadmap and platform strategy
Seniority
Founding, hands-on IC with strategic ownership