Senior Data & ML Engineer – Surgical Computer Vision
Role summary
Torus Biomedical is seeking a Senior Data & ML Engineer specializing in Surgical Computer Vision to develop a real-time AI guidance system for orthopedic surgery. This role involves architecting high-performance ML models for intraoperative X-ray and Fluoroscopy analysis, focusing on semantic segmentation, landmark detection, and feature extraction. The ideal candidate will have 5-10+ years of hands-on experience in ML, Computer Vision, or Medical Imaging, with mastery of Python, PyTorch, OpenCV, and NumPy. Responsibilities include translating clinical objectives into elegant architectures, rapid empirical iteration, and developing innovative solutions for noise and occlusion challenges in surgical environments. This position offers elite technical ownership and direct clinical impact.
Torus Biomedical is developing a real-time AI guidance system for orthopedic surgery using standard intraoperative X-ray and Fluoroscopy. By eliminating the need for pre-operative CT scans and external tracking hardware, we provide surgeons with a high-precision, digital-first workflow. This is a production-grade platform designed for immediate clinical impact, moving beyond research prototypes into real-world surgical environments.
The Innovation Environment
Our goal is to transform how intraoperative imaging is conventionally utilized. We are leveraging AI to overcome the inherent limitations of standard 2D systems, converting qualitative radiographic data into reliable, 3D quantitative assessments. We are seeking a Senior Engineer with the technical maturity to refine complex system requirements into elegant architectures and the intellectual curiosity to develop solutions that establish new global benchmarks for Surgical AI.
Core Responsibilities
- Architectural Leadership:
Translate high-level clinical objectives into high-performance ML architectures. Lead the technical path forward as we optimize for the dynamic variables of the operating room.
- Rapid Empirical Iteration:
Systematically evaluate and benchmark multiple architectural hypotheses. Move from literature to functional prototypes in days, utilizing a high-frequency
test-fail-learn
cycle to converge on optimal solutions.
- Computer Vision & Medical Imaging:
Design and scale robust pipelines for
radiographic image analysis
, specifically focusing on high-precision
semantic segmentation
,
landmark detection
, and
feature extraction
from Fluoroscopy.
- Cross-Domain Synergy:
Collaborate deeply with our leads in
Advanced Image Processing
and
3D Pose Estimation
to ensure a seamless, unified system.
- Algorithmic Innovation:
Develop original, "out-of-the-box" solutions to address noise, occlusion, and surgical artifacts, consistently outperforming existing market standards.
Required Mindset & Qualifications
- Execution-First Approach:
5–10+ years of hands-on experience in
Machine Learning
,
Computer Vision
, or
Medical Imaging
.
- Implementation Speed:
A proven track record of rapidly translating research papers into working, production-ready code.
- Problem-Solving Mastery:
The ability to move beyond standard academic frameworks to invent specific engineering solutions required for surgical success.
- The Technical Core:
Mastery of
Python
,
PyTorch
,
OpenCV
, and
NumPy
.
- Radiographic Literacy:
Deep understanding of 2D/3D image data (
X-ray
,
Fluoroscopy
,
CT
) and proficiency with visualization tools such as
3D Slicer
,
VTK
, or
SimpleITK
.
Why Join Us?
- Elite Technical Ownership:
You will own the ML and data backbone of a system that fundamentally changes surgical outcomes.
- High-Velocity R&D:
We value bold, validated thinking and rapid deployment over corporate inertia.
- Direct Clinical Impact:
Your work will be utilized by surgeons in real operating rooms where reliability and accuracy are the only metrics of success.