Grow Therapy is on a mission to serve as the trusted partner for therapists growing their practice, and patients accessing high-quality care. Powered by technology, we are a three-sided marketplace that empowers providers, augments insurance payors, and serves patients. Following the mass increase in depression and anxiety, the need for accessibility is more important than ever. To make our vision for mental healthcare a reality, we’re building a team of entrepreneurs and mission-driven go-getters. Since launching in February 2021, we’ve empowered more than ten thousand therapists and hundreds of thousands of clients across the country and insurance landscape. We’ve raised more than $328Mm in funding, including our Series D, at a $3B valuation from Sequoia Capital, Transformation Capital, TCV, SignalFire, Menlo Ventures, Goldman Sachs Alternatives, and others.

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.

Research shows that some groups hesitate to apply unless they meet every qualification. If you’re excited about this role but don’t check every box, we encourage you to apply. At Grow, we value diverse experiences, transferable skills, and the unique strengths each person brings.

Grow Therapy is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

Use of AI Tools: By submitting your application, you acknowledge and consent to the use of automated tools as part of our recruitment process. Specifically, we use a third-party AI tool, Gem, to assist in the initial screening of resumes. This tool analyzes resumes based on role-specific criteria provided by our recruiters to identify potentially strong matches for the role. Importantly, no hiring decisions are made by the AI tool. All decisions about which candidates move forward are made by our human recruiting team after independent review.More information about Gem’s approach to compliance with California FEHA regulations on automated decision systems and New York Local Law 144 can be found on the Gem compliance website.We are committed to transparency and fairness in our hiring practices. If you have questions about how our AI tools work, or would like more information about how your application will be processed, please contact us at talentops@growtherapy.com. If you require an accommodation due to a disability, or have concerns about the use of AI in the hiring process, please also contact us. We are happy to provide assistance or offer an alternative method of participating in the recruitment process.

Staff Software Engineer - ML Platform