AI Engineer - Surgical Robotics

Location: Montpellier, France (primarily on-site, 1–2 WFH days possible)

About the role

Join a fast-growing surgical robotics startup building intelligent assistance that helps surgeons in real time and improves patient outcomes. You will be the first dedicated AI hire in a small incubation team, reporting to the founder, shaping the AI roadmap, and writing hands-on code that reaches the clinic.

What you will do

• Design and implement ML and computer vision algorithms for real-time surgical assistance, including scene and instrument understanding and performance metrics
• Build data pipelines for surgical video and sensor data, including cleaning, annotation workflows, and quality checks
• Prototype and validate models with surgeons on a robotic platform and iterate quickly on proof-of-concept modules
• Define AI infrastructure and best practices for training, validation, versioning, and documentation
• Collaborate with software, robotics, and clinical stakeholders and evaluate third-party algorithms for integration

Why this is exciting

• Greenfield ownership. Establish the AI foundations and deliver the first assistance modules that surgeons will trial frequently
• Direct impact. Your work feeds into clinical use on a novel microsurgery robot
• Variety. Expect roughly a 50 50 split between setting up pipelines and heads-down coding, trending to more coding as the platform matures

What you will bring

• 2–5 years of experience in ML/AI or computer vision. Strong Python and solid C++
• Hands-on with PyTorch or TensorFlow, OpenCV, NumPy and Pandas
• Strong CV and deep learning fundamentals, plus practical experience taking models from prototype to production
• Proactive, curious builder who tracks the latest AI advances and enjoys shipping working systems

Nice to have

• Background in medical devices, surgical robotics, or regulated environments
• Experience with real-time inference, edge or embedded deployment, or cloud training stacks
• Familiarity with data governance and annotation strategies for sensitive data

Working style

Primarily on-site in Montpellier. Small, high-trust team with fast feedback loops and regular access to clinical users.

Compensation and growth

Competitive salary, meaningful equity, benefits, and conference budget. Clear path to grow into a lead role as the team scales.

How to apply

Send your CV or portfolio link and a short note on a CV or ML project you are proud of.