About Us
At SimplePractice, our team is dedicated to improving the health and wellness industry by building a suite of innovative solutions for practitioners and their clients. Our product supports practitioners on their clinical journey to becoming licensed, helps them manage their business and practice once they’re up and running, and enables new clients to discover and interact with practitioners. Taking a practitioner-first approach in everything we do makes it possible for health and wellness practitioners to devote more time to their clients while they use SimplePractice to start, grow, and maintain a successful private practice.
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 Senior 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 product features, your work will have a direct and meaningful impact.
Key Responsibilities
- AI Prototyping and Development
- Develop AI workflows, customize data pipelines, tune models, and engineer prompts to bring idea to prototype
- Work with subject matter experts to set up evaluation for AI workflows, ensuring rigor, quality and safety of content output
- Work with eng 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 user perspective
- Decompose problems into conquerable pieces. Design solutions to address each with cross-disciplinary thinking and big picture in mind.
- Conduct exploratory data analysis to answer key questions and test assumptions. Design experiments and build prototypes for proof-of-concept.
- Build artifacts to illustrate the findings with rigor and how they inform the roadmap and decisions
- Cross-Functional Collaboration
- Provide AI expert advice to product and eng partners in shaping product roadmap
- Partner closely with software eng, product, data eng, ML platform teams to scope and plan in execution
- Communicate timeline, milestones, findings w/ internal stakeholders
- Mentor & Advocate Best Practices
- Guide less experienced team members, sharing knowledge on LLM workflows and 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
- Look for creative ways to leverage data to make clinicians’ lives 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 proven track record of bringing ideas to life, from prototype to productized features
- Strong proficiency in Python and hands-on with advanced data analysis tools
- Strong skills in data engineering and self-sufficient in data pipelines for the AI workflow
- 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 in solving problems
- Comfort working with remote teams, using GitHub, Slack, Notion, and Zoom
- Proficiency in English with strong communication and collaboration skill
Bonus Points
- Experience with RAG architecture and context/state management for LLMs
- Familiarity with LLM eval tools and human-in-the-loop evaluation process
- 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, clinical workflows, or regulated domains
Base Compensation Range
$197,500 - $241,000
Base salary is one component of total compensation. Employees may also be eligible for an annual bonus or commission. Some roles may also be eligible for overtime pay.
The above represents the expected base compensation range for this job requisition. Ultimately, in determining your pay, we’ll consider many factors including, but not limited to, skills, experience, qualifications, geographic location, and other job-related factors.
Benefits
We offer a competitive benefits program including:
- Medical, dental, vision, life & disability insurance
- 401(k) plan with company match
- Flexible Time Off (FTO), wellbeing days, paid holidays, and summer Fridays
- Mental health resources
- Paid parental leave & Backup Care
- Tuition reimbursement
- Employee Resource Groups (ERGs)
California Job Applicant Privacy Notice
Thank you for your interest in opportunities at SimplePractice LLC (“SimplePractice” or “us” or “we” or “our”). Please note that when you submit your resume or application materials to us for employment purposes, you are subject to the SimplePractice California Job Applicant Privacy Notice.
For more information about our privacy practices, please contact us at [email protected].
