Member of Technical Staff, Compiler

true-talent-solutions-partners; United States; A distancia; USD 250.000 - 400.000; Jornada completa

Descripción de la vacante

True Talent Solutions Partners is seeking an engineering researcher to build a production compiler turning healthcare standards into executable decision logic. You will design representations for guideline logic and run experiments comparing models, guided by clinician collaboration and formal verification methods.

The role emphasizes rigorous experimentation, production delivery, and traceable, verifiable clinical recommendations. Remote work with US/Canada collaboration is supported.

Formación

• 3+ years of research or industry experience, or final-year PhD or postdoctoral experience.
• Experience shipping ML or NLP systems to production with Python, PyTorch, and Transformers.
• Experience with LLM evaluation, training, or prompt engineering, with evidence-based communication of failures and uncertainty.
• Bachelor's degree or higher in computer science, machine learning, mathematics, or a related technical field.
• Familiarity with compilers, program synthesis, formal methods, static analysis, IR design, constraint solving, SAT/SMT, or DSLs is valuable.
• Healthcare, safety-critical, or regulated-domain experience is beneficial.
• Must be authorized to work in the United States or Canada, and willing to attend in-person offsites several times per year.
• Comfort working through ambiguity and collaborating across disciplines, with a commitment to validating model outputs.

Responsabilidades

• Build and improve a pipeline for parsing clinical standards, transforming their content, and validating executable modules.
• Design and refine a representation for guideline logic, including exclusions, precedence, and recommendations.
• Compare open and closed models, fine-tuning approaches, and constrained decoding through well-designed experiments.
• Develop benchmarks, datasets, metrics, and adversarial cases to assess source fidelity, logical completeness, and recommendation correctness.
• Work with clinicians and technical leaders to investigate model failures and improve the production system.
• Develop deterministic validators using static analysis, constraint solving, or formal methods to surface ambiguity and contradiction.

Conocimientos

Python

PyTorch

Transformers

LLM evaluation

Educación

Bachelor's degree or higher in computer science, machine learning, mathematics, or related field

Herramientas

Static analysis tools

Constraint solving

SAT/SMT

Descripción del empleo

ABOUT THE ROLE

Join a clinical AI team building a production compiler that turns healthcare standards into structured, executable decision logic. This research-focused engineering role combines rigorous experimentation with production delivery, helping make clinical recommendations traceable, complete, and verifiable.

WHAT YOU'LL DO

• Build and improve a pipeline for parsing clinical standards, transforming their content, and validating executable modules.
• Design and refine a representation for guideline logic, including exclusions, precedence, and recommendations.
• Compare open and closed models, fine-tuning approaches, and constrained decoding through well-designed experiments.
• Develop benchmarks, datasets, metrics, and adversarial cases to assess source fidelity, logical completeness, and recommendation correctness.
• Work with clinicians and technical leaders to investigate model failures and improve the production system.
• Develop deterministic validators using static analysis, constraint solving, or formal methods to surface ambiguity and contradiction.

WHAT WE'RE LOOKING FOR

• At least 3 years of research or industry experience, or final-year PhD or postdoctoral experience.
• Experience shipping ML or NLP systems to production, with production-level Python, PyTorch, and Transformers skills.
• Experience with LLM evaluation, training, or prompt engineering, and a clear, evidence-based approach to communicating failed experiments and uncertainty.
• A bachelor's degree or higher in computer science, machine learning, mathematics, or a related technical field.
• Experience at a frontier AI lab; familiarity with compilers, program synthesis, formal methods, static analysis, IR design, constraint solving, SAT/SMT, or DSLs is valuable.
• Healthcare, safety-critical, or regulated-domain experience is beneficial.
• Must be authorized to work in the United States or Canada, and willing to attend in-person offsites several times per year.
• Comfort working through ambiguity and collaborating across disciplines, with a commitment to validating model outputs.

COMPENSATION & BENEFITS

Base salary: $250,000 to $400,000 USD annually. Visa sponsorship is not available.

LOCATION

Remote, with the primary location in Canada. Candidates may also work remotely from the United States.