Senior Machine Learning Engineer, 3D Vision

About Hike Medical

Hike Medical is building the defining company in musculoskeletal care. We sit at the intersection of AI, robotics, and healthcare, operating across three product lines: a proprietary AI-vision platform that turns a 30 second web-based foot scan into custom 3D-printed orthotics, an AI agent platform that automates the entire DME workflow from pre-visit processing to claims and revenue cycle, and SoleForge, our vertically integrated 3D printing factory producing custom medical devices at a scale the industry has never seen.

Our customers are both the largest employers on earth and the biggest companies in orthotics and prosthetics. On the clinical side, we're live across the industry's largest national providers. On the employer side, Fortune 50 companies trust us to protect their on-their-feet workforces.

But custom insoles are just the wedge. Our long-term vision is bionics: AI-designed, robotically manufactured orthotic and prosthetic devices at scale, replacing a fragmented, manual industry that hasn't changed in decades. Insoles today, full DME tomorrow, bionics by 2040. Read the full vision at bionics2040.com.

We've stealthily raised $22M through Seed and Series A backed by top-tier investors who invested early in companies like OpenAI, Anduril, and Mercury. We run a fast, results first, high ownership culture out of our new SF Rincon Hill office. If you want to work on problems that sit at the frontier of AI, manufacturing, and healthcare, this is the place.

The Role

As a Senior Machine Learning Engineer, you will bridge the gap between raw computer vision and physical, 3D-printed reality. You will own the pipeline that translates a smartphone video into a high-fidelity, CAD-compatible 3D reconstruction of human anatomy.

What You'll Work On

• 3D Reconstruction & Generation: Develop and deploy SOTA models for 3D human body part reconstruction (SDFs, NeRFs, Gaussian Splatting, or Mesh-based approaches) from videos.
• Deep Learning: Architect pipelines that handle non-Euclidean data to extract precise clinical measurements from noisy real-world scans.
• CAD Integration: Bridge the gap between AI inference and parametric CAD modeling for automated 3D printing preparation.
• Rapid Prototyping & Continual Learning: You should be used to keeping up to date on latest advances and quickly implementing these advancements into our systems.
• Production ML: Work with our engineering team to deploy models into our AWS/serverless environment, ensuring clinical-grade accuracy at scale.

Ideal Candidate Profile

Technical Requirements

• PhD in Machine Learning, Computer Graphics, Geometry Processing, or a related field, or equivalent experience.
• Deep expertise in 3D representations (Meshes, Point Clouds, Voxels, SDFs) and their respective computational tradeoffs.
• Proven track record in Generative Vision, 3D Reconstruction, or related topics.
• Strong proficiency in Python and PyTorch.
• Experience in CAD and computational geometry is a big plus.
• Experience with ML infrastructure in AWS (SageMaker, Lambda, etc) and model deployment is a plus.
• Experience in Biomedical AI or Biomechanics (e.g., modeling joint movement or tissue) is highly valued but not required.

Helpful Characteristics

• Fast Iteration Mindset: Willingness to move fast, iterate confidently in ambiguous tasks and deliver results from imprecise instructions or requirements.
• Product Minded: Our AI team communicates the art of the possible. Having a good eye for high-value product opportunities is a major plus.
• Polymathic: You can discuss loss functions with researchers, API latency with engineers, and 3D printing constraints with manufacturing.
• Strong Communicator: You clearly explain your ideas, challenge assumptions, and collaborate across engineering, AI, and product teams.
• Mission-Driven: You want to build technology that helps people walk without pain and revolutionize the future of orthopaedic care.
• Thrives in Collaboration: You push back, ask tough questions, and elevate the team.