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Compiled Health - Member of Technical Staff, Compiler (Remote)

  • Canada, United States
  • Remote
  • Posted Oct 13, 2026
  • 1 position

US$250,000–US$400,000 / year

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Employment type
Full-time
Experience level
Mid-level · 2+ years
Minimum education
Master’s degree
Posting language
English
Working hours
40 hours per week
Location requirements
Country, Canada

Job summary

You will build pipelines to convert clinical standards into executable modules and design the target syntax for guideline logic. Additionally, you will run experiments with various models and develop deterministic validators to ensure recommendation correctness.

Job details

Source: Paraform - https://www.paraform.com/share/compiled-health/cmtsxkxh100150cl7imvz606z Compensation: $250,000-$400,000 base + competitive equity (up to 5% for a frontier-lab candidate, from a 15% pool; cash/equity ratio flexible) + health, dental, vision, flexible PTO, paid parental leave. Location: Remote - US or Canada, with offsites several times a year. Visa: not open to visas (possible exceptions for frontier-lab employees). About this role Research role with production stakes: study how far frontier models can be pushed in extracting, structuring and proving clinical logic, design the experiments that settle what works, and ship the winning approach into the clinical compiler, which is live in Canadian public health care today. Ideal for someone who has published in clinical AI, wants out of the demo cycle, and believes clinical decision logic must be inspectable. What you'll do Build the pipeline converting clinical standards into executable modules: parsing with document and layout models, transformation, validation Design and iterate the target syntax/representation for guideline logic (exclusions, precedence, recommendations) Run experiments: open vs closed models, fine-tuning, constrained decoding Co-design benchmarks and adversarial cases measuring source fidelity, logical completeness and recommendation correctness; error analysis Develop deterministic validators using static analysis, constraint solving or formal methods to surface ambiguity, contradiction and source silence Work directly with the founders and the clinicians who validate the outputs; turn model failures into hypotheses and better system design Tech stack Python, PyTorch, Transformers, LLMs, Static Analysis, SMT/SAT Solvers, FHIR, HL7 v2 About Compiled Health Clinical AI research and formalization company compiling the standard of care into deterministic, evidence-traceable decision artifacts; compiler live in Canadian public health care. Founded by a physician who worked with OpenAI's health safety research team. ~6 people, founded 2024, $3M seed plus a committed billionaire family office. 3+ years of research or industry experience, or final-year PhD / postdoc Published in clinical AI (strongly preferred) Python, PyTorch, Transformers/LLMs; static analysis, SMT/SAT solvers; FHIR / HL7 v2 a plus US or Canada based; US citizen/Green Card (visa exceptions possible for frontier-lab employees)

What you’ll do

You will build pipelines to convert clinical standards into executable modules and design the target syntax for guideline logic. Additionally, you will run experiments with various models and develop deterministic validators to ensure recommendation correctness.

Requirements

Candidates should have at least 3 years of research or industry experience, or be a final-year PhD/postdoc. Proficiency in Python, PyTorch, and LLMs is required, with a strong preference for those who have published in clinical AI.

Benefits

  • Competitive equity
  • Health insurance
  • Dental insurance
  • Vision insurance
  • Flexible PTO
  • Paid parental leave

Listed skills

  • Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

  • Python
  • PyTorch
  • Transformers
  • LLMs
  • Static analysis
  • SMT solvers
  • SAT solvers
  • FHIR
  • HL7 v2
  • Clinical AI
  • Constraint solving
  • Formal methods
  • Data parsing
  • System design
  • Clinical logic
  • Transformer (Machine Learning Model)
  • Fine-tuning (Deep Learning)
  • OpenAI
  • AI Research
  • Fast Healthcare Interoperability Resources (FHIR)
  • Research
  • Artificial Intelligence
  • Static Program Analysis
  • Deterministic Methods
  • Logic Synthesis
  • Error Analysis (Numerical Analysis)
  • Python (Programming Language)
  • Parsing
  • Syntax
  • Systems Design
  • Formal Methods
  • PyTorch (Machine Learning Library)

Job areas

  • Technology
  • Software
  • Science & Research
  • Healthcare
  • Data & Analytics
  • Member of Technical Staff
  • Artificial Intelligence Engineer (General)
  • Software Developers

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