Software Engineer - ML Platform

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 $328

Mm in funding, including our Series D, at a $3B valuation from Sequoia Capital, Transformation Capital, TCV, Signal Fire, Menlo Ventures, Goldman Sachs Alternatives, and others.

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.

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.

• 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

• 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,…