Staff, Machine Learning Engineer at fullscript

About Fullscript We’re an industry-leading health technology company on a mission to help people get better. We started in 2011 with one simple idea. Make it easier for practitioners to access the products they trust so they can deliver better care. That simple idea grew into a platform that powers every part of care. Today, more than 125,000 practitioners use Fullscript for clinical insights, lab interpretations, patient analytics, education, and access to high-quality supplements. Over 10 million patients rely on Fullscript to stay connected to their care plans and follow through on treatment. We build tools that make care smarter and more human. Tools that save time, simplify decisions, and help practitioners stay closely connected to the people they care for. When everything they need is in one place, they can focus on what matters most: helping people get better. This is your invitation. Bring your ideas, your grit, and your care for people. Join us and shape the future of care. The role We’re hiring a Staff Machine Learning Engineer to join our AI team and help shape the next generation of Fullscript’s AI-powered experiences. You’ll work on building innovative AI capabilities that help clinicians provide better services and help patients improve their health. This is a senior individual contributor role for someone who can go beyond implementation. In addition to building high-quality systems, you’ll help define technical direction, guide architecture decisions, and identify where AI can create meaningful value in clinical workflows. You’ll work with a high degree of autonomy and partner closely with engineering, product, analytics, and medical stakeholders to deliver scalable, reliable, and clinically useful AI experiences. 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: SalaryFlexible PTO & competitive pay—rest fuels performance. RRSP match & stock options—invest in your future. Customizable benefits—flexible coverage, paramedical services, and an HSA. Fullscript discounts—save on wellness products. Continuous learning—training budget + company-wide initiatives. Wherever You Work Well—hybrid and remote flexibility. Why Fullscript Great work happens when people feel supported, trusted, and inspired. At Fullscript, we stay curious and keep finding smarter ways to make care better. We grow together, take on new challenges, and focus on impact. We put people first, work as a team, and leave egos at the door. What to Know Before You Apply We’re grateful for the interest in joining Fullscript. To make sure your application reaches our hiring team, please apply directly through our careers page. We’re not able to respond to individual messages about open roles on email or social channels. Fullscript is an equal opportunity employer committed to creating an inclusive workplace. Accommodations are available upon request at [Upgrade to PRO to see contact]. All offers are contingent on successful background checks conducted in compliance with federal, state, and provincial laws. We use AI tools to support parts of the hiring process, including screening and reviewing responses. Final hiring decisions are always made by people and follow all applicable privacy and employment laws in Canada and the U.S. Learn More www.fullscript.com @fullscriptHQ on instagram Let’s make healthcare whole