At SimplePractice, we are dedicated to empowering clinicians through data-driven innovations. We are looking for a Machine Learning Engineer to build product features that help clinicians work effectively and efficiently. You will design experiments, build robust models, tune prompts, implement LLM evals, and drive projects from idea to prototype to production with product, engineering, and DevOps teams.
What You'll Do
- Develop AI workflows, customize data pipelines, tune models, and engineer prompts to bring ideas to prototype.
- Work with subject matter experts to set up evaluation for AI workflows, ensuring rigor, quality, and safety of content output.
- Partner with engineering 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.
- Start with the Job-to-be-done, dive deep into the domain, and understand problems from the user perspective.
- Decompose problems and design solutions with cross-disciplinary thinking and the big picture in mind.
- Conduct exploratory data analysis, design experiments, and build proof-of-concept prototypes.
- Build artifacts to illustrate findings with rigor and inform roadmap decisions.
- 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 execution.
- Communicate timelines, milestones, and findings to internal stakeholders.
- 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.
- Stay current with emerging ML tools and technologies, integrating new techniques that elevate our product capabilities.
- Look for creative ways to leverage data to make clinicians’ lives easier, more efficient, and more effective.
What We're Looking For
- 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 bringing ideas to life from prototype to productized features.
- Strong proficiency in Python and hands-on experience with advanced data analysis tools.
- Strong skills in data engineering and self-sufficiency in building 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 strong 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.
Nice to Have
- Experience with RAG architecture and context/state management for LLMs.
- Familiarity with LLM eval 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.
Technical Stack
- Python, AWS
- GitHub, Slack, Notion, Zoom
- LLM workflows, vector databases
- Kubernetes, Argo Flows, Langfuse
Team & Environment
You will work cross-functionally with product, engineering, data engineering, ML platform, and DevOps teams.
Benefits & Compensation
- 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
- A relocation bonus for candidates joining us from a different city
- Employee Resource Groups (ERGs)
Work Mode
This role offers a hybrid work schedule.
We are an equal opportunity employer.
