Resumen del rol

Staff, Machine Learning Engineer

Requisitos y responsabilidades

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What you'll do

  • Lead the design, development, and deployment of production, multi-turn LLM-powered features, including summarization tools and clinician-facing conversational agents that support follow-up questions and reasoning over clinical context
  • Own backend services in Python that integrate LLM agents with Fullscript’s platform and support reliable production use
  • Help define technical direction for prompting, grounding, safety, and orchestration strategies used across clinical AI workflows
  • Establish and improve evaluation approaches for LLM outputs, including accuracy, hallucinations, edge cases, and overall feature quality
  • Shape engineering patterns for model-related workflows, including testing, CI/CD, observability, and version control
  • Partner with medical, product, and engineering teams to identify high-value opportunities for AI and turn them into practical, scalable product capabilities
  • Work cross-functionally with engineering, analytics, and medical SMEs to refine requirements and ensure data and system design support clinical use cases
  • Provide technical leadership across projects by creating clarity in ambiguous problem spaces, guiding tradeoff decisions, and raising the quality bar for the team
  • Stay current with the latest LLM research and emerging AI technologies, and help assess where they can be applied effectively at Fullscript

What you bring to the table

  • 6+ years of experience building and implementing machine learning applications in production, including meaningful experience with LLM-powered agents, conversational experiences, or agent-based workflows
  • A track record of owning complex technical problems end to end and shaping implementation beyond your immediate code contributions
  • Experience designing and deploying AI systems that answer open-ended questions, support follow-up interactions, and operate reliably in production
  • Strong experience with LLM application frameworks and tooling, such as LangChain, LangGraph, or similar orchestration and RAG frameworks
  • Familiarity with evaluation and monitoring frameworks for LLM outputs, conversational quality, and system reliability
  • Knowledge of MCP, agent orchestration patterns, or related approaches for building multi-step AI systems
  • Strong proficiency in Python and SQL
  • Experience making sound technical decisions around quality, safety, maintainability, and scalability in production AI systems
  • Strong communication and collaboration skills, with the ability to work effectively across technical and non-technical stakeholders

Bonus if you have

  • Experience defining technical direction for AI or machine learning systems across multiple projects or teams
  • Experience building clinician-facing, healthcare-adjacent, or other high-trust AI experiences
  • Experience with recommendation systems, personalization, or other applied ML systems beyond LLMs
  • Experience with modern retrieval, grounding, or evaluation patterns for LLM applications
  • Experience working closely with domain experts to build systems in complex or highly contextual problem spaces

What we can offer you

  • Competitive Salaries
  • Remote-first flexibility to work where you work best, with Ottawa, Toronto, or Calgary preferred for this role.
  • 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
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FocoMachine Learning EngineeringÁrea del rol
Señal de senioritySeniorNivel del candidato
StackCI/CD, LLM, PythonSkills principales
Ubicación1 país aceptadoElegibilidad

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