Job type: Permanent
Salary: $180K - $260,000 + Equity
Role Location: San Francisco, United States
The Company:
We’re partnering with a well-funded, fast-scaling healthtech startup reinventing musculoskeletal care using proprietary AI and 3D-printing technology.
The business has developed a web-based, sensor-free AI vision platform that transforms a 30-second scan into a clinically approved, precision-manufactured medical device. Already trusted by Fortune 50 employers, major health systems, and national manufacturers, the platform is expanding access to preventative care for hundreds of thousands of Americans.
Fresh off a stealth funding round led by top-tier VCs, the company is:
- Growing 10x year-over-year
- Profitable month over month
- Scaling rapidly toward $100M ARR
- Operating with a high-ownership, execution-first culture out of Boston
This is a rare opportunity to join at a true inflection point - early enough to shape the company, late enough to have real traction.
Role and Responsibilities:We’re hiring a Senior Machine Learning Engineer to design and build parametric, procedural CAD pipelines that generate custom orthopedic devices from anatomical landmarks and clinical parameters.
Partner with clinicians and design experts to extract domain knowledge and translate it into explicit parameter spaces, constraints, and rules that can be automated.
Build a maintainable library of parametric components and design primitives that generalize across products and extend into new device categories such as orthotics and prosthetics.
Work with the AI team to define the interface between learned components, such as landmark estimation and parameter prediction, and the rule-based CAD layer.
Develop geometric tooling including freeform surfaces, trimlines, top-surface estimation, offsets, and feature placement to produce clinically correct, manufacturable geometry.
Drive geometry programmatically through CAD and geometry APIs and kernels, moving beyond GUI-based workflows toward automated, high-throughput modeling.
Own the bridge from design to manufacturing, ensuring outputs are printable and meet quality requirements, and help automate design QC
- 5+ years building parametric and procedural CAD systems, ideally in a product or manufacturing context.
- Strong programmatic CAD experience, scripting and automating geometry rather than working through a GUI, using tools such as Rhino/Grasshopper, Onshape API, SolidWorks API, Fusion API, or similar Solid command of geometric modeling fundamentals including NURBS, B-Rep, meshing, and surface/solid operations.
- Proficiency in Python, TypeScript, C++, or another programming language.
- A collaborative, translational mindset, comfortable working with clinicians and designers to turn expert intuition into precise, parameterized systems.
- Ability to work well in an early-stage, fast-moving environment where the problem space is still being defined
- Experience with geometric modeling kernels such as OpenCascade or Parasolid
- Experience with implicit geometric representations Experience with simulation-in-the-loop design, shape optimization, or topology optimization
- Familiarity with CAD interoperability standards such as STEP, IGES, or JT Exposure to AI-driven or generative CAD workflows, enough to collaborate effectively with an ML team
- Background in footwear, orthotics, prosthetics, dental, medical devices, or another domain that maps anatomy to custom physical products
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