Machine Learning Engineer, Applied AI (Hybrid)SimplePractice • Los Angeles, California, United States
Machine Learning Engineer, Applied AI (Hybrid)
SimplePractice
- Los Angeles, California, United States
- Los Angeles, California, United States
Über
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
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Sprachkenntnisse
- English
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