Research Engineer (Fully Remote)

HealthTech Company; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

HealthTech Company is seeking a researcher/engineer to build a production compiler that turns clinical standards into executable, traceable decision logic. The team is research-focused and collaborates across clinicians to improve reliability of clinical decision systems.

The role involves parsing standards into validated modules, evaluating models, benchmarking, and shipping improvements using deterministic validators. Willingness to attend in-person offsites is expected.

Qualifications

• 3+ years research/industry or final-year PhD/postdoc with production engineering experience.
• Strong Python, PyTorch, Transformers, and LLM evaluation skills.

Responsibilities

• Parse clinical standards into validated executable modules and refine guideline logic representation.
• Evaluate models, create benchmarks, and ship improvements using deterministic validators.

Skills

Python

PyTorch

Transformers

LLM evaluation

Education

PhD/postdoc or equivalent production engineering experience

Job description

• Build a production compiler turning clinical standards into executable, traceable logic.
• Improve the reliability and inspectability of clinical decision systems.

Responsibilities:

• Parse clinical standards into validated executable modules and refine guideline logic representation.
• Evaluate models, create benchmarks, and ship improvements using deterministic validators.

Requirements:

• 3+ years research/industry or final-year PhD/postdoc with production engineering experience.
• Strong Python, PyTorch, Transformers, and LLM evaluation skills.

Culture:

• Research-focused, cross-disciplinary collaboration with clinicians.
• Comfort with ambiguity; willingness to attend in-person offsites multiple times a year.

This healthtech company builds a production compiler that turns clinical standards into executable, traceable decision logic. The team is research-focused and collaborative, working across disciplines to improve the reliability of clinical decision systems.