Senior Machine Learning Engineer

Summary

Join SimplePractice as a Senior Machine Learning Engineer and leverage data to optimize clinician workflows. Develop and deploy ML pipelines, optimizing models for performance and scalability. Lead advanced analyses to drive product decisions and collaborate with cross-functional teams. Communicate complex results clearly and mentor junior team members. Champion a culture of experimentation and innovation, staying current with emerging ML tools and technologies. Your work will directly impact clinicians' daily experiences, making their lives easier and more efficient.

Requirements

• Proficiency in Python (NumPy, Pandas, scikit-learn)
• Strong skills in SQL (window functions, advanced queries)
• Hands-on experience with DBT for data transformation
• Familiarity with Snowflake or similar data warehouses
• Experience with AWS (or other cloud platforms) for model deployment

Responsibilities

• Develop & Deploy ML Pipelines Build end-to-end solutions—from data exploration to model deployment—that enhance clinician experiences
• Optimize and maintain models for performance, reliability, and long-term scalability
• Lead Advanced Analysis Conduct deep-dive analyses, uncovering insights that drive product decisions
• Collaborate with product teams to turn data into actionable next steps
• Cross-Functional Collaboration Work closely with Engineering, Product, and Design to ensure ML features are intuitive, impactful, and aligned with clinician needs
• Communicate complex results clearly to both technical and non-technical partners
• Mentor & Advocate Best Practices Guide less experienced team members, sharing knowledge on model development, MLOps, and data engineering
• 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

Preferred Qualifications

• Exposure to Outerbounds or similar ML orchestration platforms
• Experience with Argo Flows for CI/CD
• Familiarity with Kubernetes for container orchestration

Benefits

• 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)