Machine Learning Engineer, Applied AI (Hybrid)

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. We are seeking a Machine Learning Engineer, Applied AI to build product features that help clinicians work efficiently and provide quality care. You’ll design experiments, build robust models, tune prompts, implement LLM evaluations, and move projects from idea to production alongside product, engineering, and DevOps teams. Responsibilities AI Prototyping and Development Develop AI workflows, customize data pipelines, tune models, and engineer prompts to bring ideas to prototypes Work with subject matter experts to set up evaluation for AI workflows, ensuring rigor, quality and safety of content output Work with engineering partners to integrate AI workflows into production Build and configure AI performance monitoring with proper reporting and alerts Optimize and maintain AI workflows for performance, reliability, and long‑term scalability Research Start with the Job‑to‑be‑done, dive deep into the domain and understand the problem from a user perspective Decompose problems into conquerable pieces; design solutions that address each with cross‑disciplinary thinking and a big‑picture focus Conduct exploratory data analysis to answer key questions and test assumptions; design experiments and build prototypes for proof‑of‑concept Build artifacts to illustrate findings with rigor and how they inform the roadmap and decisions Cross‑Functional Collaboration Provide AI expert advice to product and engineering partners in shaping the product roadmap Partner closely with software engineering, product, data engineering, and ML platform teams to scope and plan in execution Communicate timeline, milestones, findings with internal stakeholders Mentor & Advocate Best Practices Guide less experienced team members, sharing knowledge on LLM workflows and the AI/ML model lifecycle Champion a culture of experimentation, continuous learning, and proactive problem‑solving Drive Innovation Stay current with emerging ML tools and technologies, integrating new techniques that elevate our product capabilities Explore creative ways to leverage data so clinicians’ lives are easier, more efficient, and more effective Desired Skills & Experience BS or above in Computer Science, Statistics or a related technical field 5+ years of experience in Machine Learning, with a proven track record of turning ideas into productized features Strong proficiency in Python and advanced data analysis tools Strong skills in data engineering and self‑sufficient data pipelines for AI workflows Experience with AWS (or other cloud platforms) for model deployment Comfortable designing and evaluating LLM‑driven workflows Familiarity with retrieval pipelines and vector databases Problem‑oriented mindset with cross‑disciplinary thinking and a bias toward simplicity and clarity Comfort working with remote teams, using GitHub, Slack, Notion, and Zoom Proficiency in English with strong communication and collaboration skills Bonus Points Experience with RAG architecture and context/state management for LLMs Familiarity with LLM evaluation tools and human‑in‑the‑loop evaluation processes Experience with Outerbounds or similar ML orchestration platforms Experience with Argo Flows for CI/CD Experience with prompt management tools like Langfuse Familiarity with Kubernetes for container orchestration Background in healthcare, clinical workflows, or regulated domains Benefits Privatized Medical, Dental & Vision Coverage Work From Home stipend Flexible Time Off (FTO), wellbeing days, paid holidays, and Summer Fridays Monthly Meal Reimbursement Holiday Bonus, 15‑day Aguinaldo Hybrid Work Schedule & Catered Lunch Relocation bonus for candidates joining from a different city Employee Resource Groups (ERGs) Base Compensation Range: $972,240 MXN – $1,215,300 MXN #J-18808-Ljbffr SimplePractice