Senior Member of Technical Staff, Compiler
New
T
True Talent Solutions PartnersClinical AI
Remote, with the primary location in Canada. Candidates may also work remotely from the United States.Full-TimeSenior
Salary250,000 - 400,000 USD per year
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Job Details
- Experience
- At least 3 years of research or industry experience, or current status as a final-year PhD student or postdoctoral researcher.
- Required Skills
- PythonMachine LearningPyTorchNLPPrompt Engineering
Requirements
- Have at least 3 years of research or industry experience, or be a final-year PhD student or postdoctoral researcher.
- Hold a bachelor's degree or higher in computer science, machine learning, mathematics, or a related technical field.
- Have production engineering experience, including shipping ML or NLP systems to production.
- Bring production-level Python, PyTorch, and Transformers ecosystem skills.
- Have experience with LLM evaluation, training, or prompt engineering.
- Have experience validating model outputs and communicating failed experiments clearly.
- Be able to work through ambiguity with cross-disciplinary teams.
- Have interest or experience in compilers, program synthesis, formal methods, static analysis, IR design, constraint solving, SAT/SMT, or DSLs.
- Healthcare, safety-critical, or regulated-domain experience is valuable; familiarity with FHIR or HL7 v2 is relevant.
- Be willing to attend in-person offsites several times per year.
Responsibilities
- Build pipelines that parse clinical standards and transform them into validated, executable modules.
- Design and refine a target syntax for representing guideline logic.
- Evaluate open and closed models, fine-tuning approaches, and constrained decoding strategies.
- Develop benchmarks, datasets, metrics, and adversarial cases to measure clinical fidelity and logical completeness.
- Analyze model failures, form hypotheses, and run experiments to improve the production compiler.
- Create deterministic validators using static analysis, constraint solving, or formal methods to identify ambiguity and contradiction.
- Collaborate with clinicians and technical colleagues on requirements and validation.
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