SimplePractice
Health Tech
MachineLearningEngineer,AppliedAI
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Machine Learning Engineer, Applied AI at SimplePractice. Skills: Machine Learning, Applied AI, LLM workflows, Data pipelines. Develop AI workflows. Customize data pipelines”
What You'll Achieve.
Turn data into meaningful outcomes; Build systems for efficiency; Build systems for insight; Build systems for intuition; Build product features for effectiveness; Build product features for efficiency; Make clinicians' lives easier
Industry & Context.
Tackling challenging problems; Problem-oriented mindset; Bias toward simplicity; Bias toward clarity
What They're Looking For.
Must Have
BS or above in Computer Science, 5+ years of experience in Machine Learning, Proficiency in Python, Hands-on with advanced data analysis tools, Experience with data engineering, Self-sufficient in data pipelines for AI workflow, Experience with AWS for model deployment, Comfort designing and evaluating LLM-driven workflows, Familiarity with retrieval pipelines, Familiarity with vector databases, Problem-oriented mindset, Cross-disciplinary thinking, Bias toward simplicity and clarity, Comfort working with remote teams, Proficiency in English
Nice to Have
Experience with RAG architecture, Experience with context/state management for LLMs, Familiarity with LLM eval tools, Familiarity with human-in-the-loop evaluation, Experience with Outerbounds or similar ML orchestration platforms, Experience with Argo Flows for CI/CD, Experience with prompt management tool like Langfuse, Familiarity with Kubernetes for container orchestration, Background in healthcare, Background in clinical workflows, Background in regulated domains
What You'll Do.
Customize data pipelines
Set up evaluation for AI workflows
Integrate AI workflows into production
Build AI performance monitoring
Optimize AI workflows
Maintain AI workflows
Research user problems
Conduct exploratory data analysis
Provide AI expert advice
Partner with software eng
Partner with data eng
Partner with ML platform teams
Scope and plan execution
Communicate milestones
Share knowledge on LLM workflows
Share knowledge on AI/ML model lifecycle
Champion experimentation culture
Champion continuous learning
Champion proactive problem-solving
Stay current with ML tools
Stay current with ML technologies
Integrate new techniques
Leverage data creatively
How You'll Work.
Team & Collaboration
Product teams; Engineering teams; DevOps teams; Eng partners; Product partners; Data eng teams; ML platform teams; Cross-disciplinary thinking
Communication Scope
Presenting insights
Process & Methodology
Roadmapping exercises
Full Job Description
About Us SimplePractice is headquartered in Los Angeles, California, but we have team members who work and live across the United States, Dominican Republic, Mexico City, and Ukraine. At SimplePractice, we are improving access to quality care by equipping health and wellness clinicians with all the tools they need to thrive in private practice. More than 250,000 providers trust SimplePractice to build their business through our industry-leading software with powerful tools that simplify every part of practice management. From admin work to clinical care, our suite of innovative solutions work together to reduce administrative burden—empowering solo and small group practitioners to thrive alongside their clients. Award-winning and people-first, SimplePractice is shaping the future of health tech. Recognized by MedTech Breakthrough, the Digital Health Awards, Best Places to Code in Mexico and Built In's Best Places to Work. The Role Our team is dedicated to empowering clinicians through data-driven innovations. We combine rigorous data science with practical engineering to build systems that make daily workflows more efficient, insightful, and intuitive. If you love tackling challenging problems and turning data into meaningful outcomes, you’ll find a welcoming and dynamic environment here. As a Machine Learning Engineer, Applied AI, you’ll be at the forefront of building product features that help clinicians work effectively and efficiently, providing quality care to patients. You’ll be designing experiments, building robust models, tuning prompts, implementing LLM evals, and driving projects from idea to prototype to production with product, engineering and devOps teams. You’ll also play an important role in the roadmapping exercises of our ML platform. We value mentorship, open communication, and pushing the boundaries of what AI can do in a real-world healthcare context. Whether you’re fine-tuning a model, presenting insights to stakeholders, or brainstorming new
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