Hike Medical is reinventing musculoskeletal care, starting with feet. Our proprietary AI-vision platform turns a 30 second web based (yes, no sensors) foot scan into precision engineered, 3D-printed insoles that prevent pain before it starts. We're already protecting on-their-feet workforces at Fortune 50 leaders, major health systems, and middle America manufacturers. Fresh off a stealthy round with top tier VCs, we run a fast, no BS, execution first culture out of Boston’s Seaport as we sprint toward $100M ARR and standing with 10M Americans as they step into their shoes daily.
First and only PDAC approved 3D printed custom insole in the world 🌎
3 Proprietary AI models that power the experience
Two products: One is focused on serving employers & health plans, and the other enables clinics to deliver foot care at a fraction of the cost - creating a virtuous cycle of clinician labelled data.
Expanded care access to over 100,000 Americans to date
10x'd revenue from 2023 to 2024, and on track to do the same in 2025. Profitable month-over-month.
The Role
Build and ship production systems that turn 3D patient data into clinical results. You’ll take work from research through deployment helping design, implement, and maintain the ML/geometry stack end to end.
What You’ll Work On:
Research and deploy cutting-edge 3D machine learning algorithms across our entire pipeline: from foot capture and reconstruction to personalized clinical orthotics design.
Curate and manage high-quality datasets, including protocol design, annotation strategies, and data versioning.
Own the full ML development lifecycle, from prototyping to production deployment.
Build and maintain developer-facing APIs and SDKs for internal and external use.
Collaborate cross-functionally with ML researchers, engineers, clinicians, and product teams to turn ideas into real-world solutions.
Prototype and integrate 3D perception and reconstruction systems, advancing the frontier of musculoskeletal care.
Technical Skills
Strong foundation in computer graphics, 3D geometry, and computer vision.
Experience working with noisy, real-world 3D data (point clouds, meshes, and multi-view captures).
Proven track record of developing and deploying 3D geometry and ML systems in production environments.
Experience with ML deployment on AWS, including SageMaker.
Tools you’ve used:
Python, PyTorch, PyTorch3D, CUDA
Geometry libs: Open3D, Trimesh, and other mesh processing libs.
CI/CD, testing, packaging.
Visualization/engines: Blender, Unity, Unreal.
Bonus Experience (Nice to Have)
Physical modelling and simulation : Experience with biomechanical or physics-based modelling, finite element methods (FEM), and anatomical simulations.
CAD & parametric design: Experience building/extending CAD tools, especially those involving parametric or procedural modelling.