Applied Machine Learning Scientist developing Generative AI and predictive ML solutions at TD, a major North American bank. Supporting model evaluation, deployment, monitoring, and responsible AI governance.
About the role
- Senior Machine Learning Engineer building LLM-powered lab interpretation and clinical decision-support tools for Fullscript’s healthcare platform. Owning AI systems from prototyping through production.
Responsibilities
- Design, build, and deploy LLM-powered product features, including lab result summaries, clinical workflow tools, and practitioner-facing conversational agents
- Build backend services integrating LLMs and ML models into Fullscript’s platform, primarily using Python and increasingly Elixir
- Develop AI systems supporting open-ended clinical questions, follow-up interactions, and reasoning over structured and unstructured healthcare context
- Implement prompting, grounding, retrieval, and safety strategies
- Build evaluation, testing, monitoring, and CI/CD workflows for AI features
- Partner with medical, product, analytics, and engineering teams to translate clinical needs into scalable AI capabilities
- Own AI systems 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 LLM, agentic AI, and applied ML ecosystems while assessing production readiness
Requirements
- 7+ 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
- Solid SQL fundamentals
- Familiarity with MCP, Langfuse, agent orchestration patterns, tool-calling systems, or multi-step AI workflows
- Experience integrating LLMs such as OpenAI, Gemini, Anthropic, or similar models into user-facing products
- Experience with 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 applications for quality, hallucinations, correctness, edge cases, and reliability
- Ability to work independently in ambiguous problem spaces and partner with technical, product, medical, and non-technical stakeholders
Benefits
- Flexible PTO
- RRSP/401k match
- Stock options
- Premium benefits package with customizable coverage
- Paramedical services
- HSA
- Fullscript discounts on wellness products
- Continuous learning opportunities
- Remote-first flexibility
- Competitive pay
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