Founding Technical Lead – Healthcare Human Data (Frontier AI)

Remote | Founding Role | Part-Time → Scalable

We are building a healthcare-focused human data company designed to support frontier AI labs in improving model reasoning, safety, and evaluation performance.

This is not an annotation startup.

We are looking for a founding technical lead who has already worked inside the frontier AI ecosystem and understands how model training pipelines actually consume human data.

Requirements:

You must have direct experience working with a frontier AI lab (e.g. OpenAI, Anthropic, Google DeepMind, Meta AI, etc.) on:

• RLHF or RLAIF
• Model evaluation
• Red teaming
• Human data pipelines
• Alignment or reasoning improvement

What You Will Own:

• Design of high-signal healthcare datasets targeting real model failure modes
• Construction of structured correction artifacts (not generic Q&A)
• Development of scoring rubrics and evaluation frameworks
• Creation of the initial validation dataset used to secure commercial contracts
• Definition of training standards for clinician contributors
• Technical credibility with frontier labs

You will be setting the bar for what “high-quality healthcare human data” means.

The Profile We’re Looking For:

• Consultant-level Doctor (or equivalent senior clinical experience)
• First-hand exposure to how frontier models ingest, filter, and score human data
• Strong intuition around model blind spots (hallucination, overconfidence, shallow reasoning, calibration errors)
• Able to think like both a clinician and a model evaluator
• High agency, startup mentality

Compensation Structure:

• Competitive consulting rate
• Performance-based upside
• Potential equity pathway based on validated impact and ARR milestones

Why This Role Is Different:

Most healthcare AI data companies compete on volume.

We compete on signal.

If you understand the difference - and have operated at that level - this will be obvious to you.