Senior Machine Learning Engineer, Platform

Summary

Join SimplePractice as a Senior Machine Learning Engineer, Platform, and be at the forefront of building tools and systems for AI engineers and developers to innovate rapidly and responsibly. You will blend creative problem-solving with hands-on technical work, building robust, scalable, and easy-to-maintain systems. Collaborate with internal stakeholders to develop the platform roadmap, communicate progress, and drive stakeholder engagement. Mentor junior team members, champion best practices, and drive innovation by staying current with emerging ML tools and technologies. You will look for creative ways to leverage data to improve clinicians' experiences. This role offers a dynamic environment where you can contribute to the technical vision and architecture of the ML Platform and share your expertise.

Requirements

• BS or above in Computer Science or a related technical field
• 7+ years of experience in software development, ideally on dev tools, with Python expertise for a part of your career
• Have experience with ML/LLM. Familiar with ML model workflow, from ideation, prototyping to deployment
• Proficiency in building data pipelines and tooling for ML feature pipelines
• Experience with AWS (or other cloud platforms) for model deployment
• Comfort working with remote teams, using GitHub, Slack, Notion, and Zoom
• Proficiency in English with strong communication and collaboration skills

Responsibilities

• Develop & Deploy ML Platform Build end to end solutions to ensure consistent tooling and governance for LLM/AI feature development
• Ability to design well-structured and performant RESTful APIs, including defining clear endpoints, request/response formats, and error handling
• Cross-Functional Collaboration Work closely with Engineering, and other internal stakeholders of ML platform to develop platform roadmap
• Properly communicate timeline, milestones, and progress w/ internal stakeholders
• Drive stakeholder engagement, enablement and education to ensure the platform is well integrated into AI dev workflow
• 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

• Experience with RAG architecture and other LLM design patterns
• Experience with pythonic asynchronous tools like Celery
• Exposure to Outerbounds or similar ML orchestration platforms
• Experience with Argo Flows for CI/CD
• Familiarity with Kubernetes for container orchestration

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
• A relocation bonus for candidates joining us from a different city
• Employee Resource Groups (ERGs)