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Senior Machine Learning Engineer
Fullscript
Remote, CAN
Full-time
Senior
Remote
CAD 140,000 to CAD 160,000.
Discovered 4 days ago
Machine learning engineeringApplied artificial intelligenceLarge language models (LLMs)PythonSQLRetrieval-augmented generation (RAG)
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Machine learning engineeringApplied artificial intelligenceLarge language models (LLMs)
Role Overview
Fullscript is hiring a Senior Machine Learning Engineer for its AI and Analytics Engineering team.
The team builds AI-powered lab interpretation, clinician decision support, and conversational experiences within the Fullscript product.
This is a senior individual contributor role focused on shipping production AI systems from experimentation through deployment, evaluation, and iteration.
Key Skills for This Role
Machine learning engineeringApplied artificial intelligenceLarge language models (LLMs)PythonSQLRetrieval-augmented generation (RAG)
Full Job Posting
About Fullscript
Fullscript is a health technology company whose platform supports practitioners with clinical insights, lab interpretations, patient analytics, education, and access to supplements.
The company builds tools intended to simplify clinical decisions and help practitioners stay connected to patient care plans.
The Opportunity
Fullscript is hiring a Senior Machine Learning Engineer for its AI and Analytics Engineering team.
The team builds AI-powered lab interpretation, clinician decision support, and conversational experiences within the Fullscript product.
This is a senior individual contributor role focused on shipping production AI systems from experimentation through deployment, evaluation, and iteration.
What You’ll Do
- Design, build, and deploy LLM-powered lab summaries, clinical workflow tools, and practitioner-facing conversational agents.
- Build Python backend services that integrate LLMs and machine learning models into the platform.
- Develop AI systems for open-ended clinical questions, follow-up interactions, and reasoning over healthcare context.
- Implement prompting, grounding, retrieval, and safety strategies for quality, consistency, and clinical relevance.
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