As a Senior Machine Learning Engineer, you will play a key role in shaping AI-powered features within a health technology platform. Your work will focus on designing, testing, and deploying multi-turn large language model (LLM) systems that support clinical reasoning and improve care delivery.
What You'll Do
- Develop and maintain production-ready LLM features such as summarization tools and interactive conversational agents capable of handling complex clinical follow-up questions.
- Design and own scalable Python backend services that integrate LLM agents into core platform workflows.
- Implement prompting strategies, grounding techniques, and safety controls to ensure reliable and context-aware model behavior in real-world clinical settings.
- Establish evaluation frameworks to monitor accuracy, detect hallucinations, and assess edge cases in LLM outputs.
- Build and maintain CI/CD pipelines and versioning systems for models and related components.
- Partner with medical experts and product teams to align AI functionality with clinical best practices and practitioner needs.
- Stay informed about advancements in LLM research and adapt new methods to improve system performance and reliability.
Requirements
- Minimum of three years of experience delivering LLM-based applications in production environments, particularly those involving conversational systems or agent-based architectures.
- Hands-on experience with LangChain, LangGraph, Hugging Face, and related frameworks for agent orchestration, tool integration, and RAG pipelines.
- Familiarity with evaluation and monitoring tools for assessing conversational quality and model output integrity.
- Working knowledge of MCP and agent orchestration platforms.
- Strong programming skills in Python and SQL, with a focus on clean, maintainable code.
- Solid grasp of data engineering principles, including testing, version control, and CI/CD practices.
- Experience building AI systems that support reasoning, open-ended inquiry, and multi-turn interactions.
- Ability to clearly explain technical concepts to both technical and non-technical audiences.
- A proactive learner who actively explores new tools, techniques, and research in the AI space.
Benefits
- Flexible paid time off and competitive compensation
- RRSP matching contributions in CAD and stock options
- Customizable benefits package including health spending accounts and coverage for paramedical services
- Employee discount on a curated catalog of wellness products for personal use and sharing with family and friends
- Annual training budget and access to company-wide learning initiatives
- Flexible work model supporting hybrid and remote work environments
