Senior Machine Learning Engineer

🕒 May 6

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Fullscript

201 - 500 employees

Founded 2016

⚕️ Healthcare Insurance

🧘 Wellness

☁️ SaaS

💰 $240M Private Equity Round on 2021-11

Healthcare Insurance • Wellness • SaaS

Fullscript is a comprehensive platform that facilitates whole person care for healthcare providers. It integrates industry-leading lab testing, high-quality supplements, and a suite of tools designed to enhance patient adherence and outcomes. Fullscript offers features like personalized patient plans, evidence-based templates, patient engagement tools, and seamless wholesale ordering of supplements. The platform also integrates with top EHR systems to streamline workflows for healthcare practitioners, making it easier for them to provide effective care. With Fullscript, patients can manage their health routines more conveniently, and providers can create personalized care plans with the support of clinical evidence and insights.

📋 Description

• Design, build, and deploy LLM-powered product features, including lab result summaries, clinical workflow tools, and practitioner-facing conversational agents. • Build backend services that integrate LLMs and ML models into Fullscript’s platform, primarily using Python, with increasing exposure to Elixir as the platform evolves. • Develop AI systems that can support open-ended clinical questions, follow-up interactions, and reasoning over structured and unstructured healthcare context. • Implement prompting, grounding, retrieval, and safety strategies that improve output quality, consistency, and clinical relevance. • Build evaluation, testing, monitoring, and CI/CD workflows for AI features, including approaches for accuracy, hallucination detection, edge cases, and reliability. • Partner with medical, product, analytics, and engineering teams to translate clinical needs into practical AI capabilities that can scale. • Own AI systems end to end, from experimentation and prototyping through production deployment, iteration, and ongoing improvement. • Contribute to architecture and implementation decisions for AI-powered analytics, lab interpretation, and clinical decision-support workflows. • Stay current with fast-moving LLM, agentic AI, and applied ML ecosystems, while staying pragmatic about what is ready for production use.

🎯 Requirements

• 5+ years of experience in machine learning engineering, applied AI engineering, backend engineering, or a similar role, with a track record of shipping production systems. • 2+ years of recent hands-on experience building LLM-powered applications, including conversational agents, RAG workflows, tool use, or agentic systems. • Strong backend development experience in Python, with solid SQL fundamentals and comfort working across data-heavy product environments. • Experience integrating LLMs such as OpenAI, Gemini, Anthropic, or similar models into user-facing products. • Experience with LLM application frameworks or orchestration tools such as LangChain, LangGraph, Hugging Face tools, or similar frameworks. • Strong engineering practices, including Git, testing, CI/CD, observability, evaluation, and production monitoring. • Experience evaluating and validating LLM-based applications for quality, hallucinations, correctness, edge cases, and reliability over time. • Ability to work independently in ambiguous problem spaces, ask strong questions, make sound tradeoffs, and partner effectively with technical, product, medical, and non-technical stakeholders. • Bonus if you have: Experience with Elixir, Phoenix, functional programming, or an interest in building with Elixir as Fullscript’s AI platform evolves. • Bonus if you have: Experience building AI assistants, conversational agents, or decision-support tools in healthcare, clinical workflows, regulated products, or other high-trust environments. • Bonus if you have: Familiarity with MCP, Langfuse, agent orchestration patterns, tool-calling systems, or multi-step AI workflows.

🏖️ Benefits

• Flexible PTO and competitive pay, because work-life balance matters • RRSP/401k match and stock options to invest in your future • Premium benefits package with customizable coverage, paramedical services, and an HSA. • Fullscript discounts to save on high-quality wellness products • Continuous learning opportunities to grow your skills and career • Remote-first flexibility to work where you work best, with Ottawa, Toronto, or Calgary preferred for this role.

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