The Opportunity

We're hiring a Staff ML Platform Engineer to drive the technical vision and execution of Grow Therapy's Machine Learning Platform. In this role, you'll design, build, and scale the real-time ML systems that power core product experiences, starting with patient-provider matching and define the architecture that will carry the platform through the next several years of growth.

You'll operate as a de facto technical decision-maker, partnering closely with Data Science, Product and Engineering to translate business goals into robust platform capabilities and setting the bar for what excellent ML infrastructure looks like at Grow.

Why This Role Matters

Matching a client to the right therapist is one of the most consequential moments in mental healthcare. It's also a hard technical problem. Grow Therapy's matching system must be fast, accurate, and personalized, operating under strict latency constraints at a scale that only grows. Getting this right means more people get better care, more providers build thriving practices, and Grow's platform delivers on its promise.

We're growing fast with nearly 22,000 clinicians, over 1.4 million clients, and on track to surpass 10 million sessions in 2026, and we're still early. The Staff ML Platform Engineer who joins now will build foundational systems that matter at meaningful scale and help define how ML is practiced at Grow for years to come.

What You'll Be Doing

• Design and build large-scale, real-time ML systems with a deep understanding of platform fundamentals, including systems that must meet strict latency requirements, such as sub-second response budgets for patient-provider matching
• Implement core ML platform components with the same rigor and code quality expected of a senior backend software engineer, including algorithmic and systems-level work
• Own critical ML infrastructure components end to end: Feature Stores, Online/Offline Parity, Deployment Safety, Monitoring, Failure Modes, and Feedback Loops
• Define the technical vision and 1-3 year roadmap for the ML platform
• Partner closely with Data Science, Product and Engineering teams, translating business goals like match rate and provider utilization into clear platform requirements, and maintaining strong communication across the modeling/platform boundary
• Drive adoption of an AI-first development mindset, reaching for AI tooling where appropriate and ensuring the platform can efficiently serve both static and live models at scale

You'll Be a Good Fit If You Have

• Proven experience designing and building real-time ML systems at scale, with the ability to clearly articulate the tradeoffs and architectural decisions behind what you've built
• Deep expertise in ML infrastructure, including Feature Stores, real-time serving, model deployment safety, monitoring, and feedback loop design
• Direct experience with real-time ranking and recommendation systems
• Experience with backend engineering fundamentals, you can write high-quality production code and engage in algorithmic problem solving
• Experience with infrastructure tooling such as Terraform and cloud-native ML serving platforms
• A demonstrated track record of technical leadership with broad organizational scope; for example you've influenced architecture decisions and raised the bar across teams, not just within one
• Natural partnership instincts; you're equally comfortable discussing business outcomes with product stakeholders and diving deep on system design with data scientists
• Experience using AI-assisted development tools and an openness to AI-first ways of working
• A bias toward ownership, rigor, and continuous improvement

Role Details:

• Employment Type: Full-Time, Exempt
• Base Compensation: The base compensation range for this position is Hybrid Commitment:
  
  $217,000-$288,000 USD Annually

This role will be hybrid (onsite from our San Francisco, Seattle or New York hub location three days per week: Tuesday, Wednesday, Thursday) and travel 2-3 times per year (e.g., company and department offsites).

The base compensation for this role will vary depending on several factors, including relevant experience, qualifications, and the candidate's working location.

Full Time Employee Benefits:

• Comprehensive Health Coverage: Medical, dental, and vision insurance, plus life and disability coverage.
• Parental Leave & Family Support: Up to 18 weeks paid leave and a new child stipend.
• Financial Wellness: 401(k) program and equity opportunities.
• Meals & Home Office Support: Stipends for home office setup and ongoing funds for meals, with tailored perks for both remote and in-office employees.
• Time Off to Recharge: Flexible PTO, 12 paid holidays, and a full winter break week.
• Wellness & Development: Annual stipends to put towards personal & professional growth.
• Mental & Physical Health Support: No-cost access to therapy through the Grow platform, weekly flexible hours for self-care ("Mental Health Mornings/Afternoons") and memberships to leading wellness apps (such as One Medical, Headspace, and Talkspace).
• Extra Perks: Pet insurance discounts, commuter benefits, and global travel assistance.