Hike Medical
Senior Machine Learning Engineer, CAD Computational Design
San Francisco, CA · Senior
Sponsorship not specified$190k-$270kDetected 15 days ago
TypeScriptPythonC++Machine LearningLogisticsSolidWorks
About the role
- Our next chapter is a CAD-driven system with AI on top - procedural, parametric models anchored to anatomical landmarks, with AI predicting the right parameters rather than generating geometry end-to-end.
Responsibilities
- 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 cleanly into new device categories (e.g., AFOs and other O&P devices).
- Collaborate with the AI team to define the interface between learned components (landmark estimation, parameter prediction) and the rule-based CAD layer.
- Develop geometric tooling - freeform surfaces, trimlines, top-surface estimation, offsets, and feature placement - that produces clinically correct, manufacturable geometry.
- Drive geometry programmatically through CAD/geometry APIs and kernels, moving beyond GUI-based workflows toward high-throughput, automated modeling.
- Own the bridge from design to manufacturing, ensuring outputs are printable and meet quality requirements, and helping automate design QC.
- 5+ years building parametric and procedural CAD systems, ideally in a product or manufacturing context. This is the core of the role and where we most need depth.
- We welcome applicants of all backgrounds and are committed to building an inclusive team.
Requirements
- Proficiency in Python, Typescript, C++ or any software programming language.
- Ability to thrive in an early-stage, fast-moving environment where the problem space is still being defined.
Nice to have
- Experience with geometric modeling kernels (e.g., OpenCascade, Parasolid).
- Experience with implicit geometric representations.
- Experience with simulation-in-the-loop design, shape optimization, or topology optimization.
- Familiarity with CAD interoperability standards (STEP, IGES, JT, or similar).
- Exposure to AI-driven or generative CAD workflows - enough to collaborate effectively with our AI team (deep ML expertise is not required
- we have that side covered).
- This is a foundational, high-leverage hire.
- Level: Open to a range of seniority
Compensation
- Competitive salary plus meaningful early-stage equity and benefits. (Range to be finalized ~$190,000-$270,000 depending on experience and level.)
Benefits
- Hike Medical is an
Equal opportunity
- Open to a range of seniority; final leveling determined during the interview process.
- Hike Medical is an equal opportunity employer.
- equal opportunity employer.
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This listing is sourced directly from Hike Medical's careers page and normalized into a canonical job model.