Surgical AI Engineer / Scientist

Scopia Surgical is an innovative MedTech startup dedicated to improving healthcare through solutions based on artificial intelligence and computer vision. We develop cutting-edge technologies for surgical treatment through medical image analysis, with the goal of significantly transforming healthcare delivery.

Position Overview

We are seeking an adaptable, high-impact Surgical AI Engineer / Scientist to develop, train and deploy deep learning models that operate directly on live endoscopic and laparoscopic video feeds and on preoperative medical imaging. You will collaborate closely with senior algorithm leads, software engineers, and clinical advisors to turn intraoperative surgical video and preoperative medical imaging into real-time perceptual intelligence.

Key Responsibilities

• Develop and refine deep learning models for endoscopic video streams and medical images.
• Use self-supervised learning, domain adaptation, and synthetic data augmentation for sparse medical datasets.
• Convert Python prototypes into low-latency inference pipelines.
• Apply standard MLOps practices for experiment tracking and dataset versioning.
• Define ground-truth protocols with clinical specialists.
• Curate and anonymize clinical datasets following HIPAA/GDPR standards.
• Write modular code and documentation adhering to IEC 62304 / ISO 13485 standards.

Essential Qualifications

Option A (Ph.D. Path) : Ph.D. in Computer Science, Biomedical Engineering, Electrical Engineering, Robotics, or a related quantitative field with a primary research focus on computer vision, medical image analysis, or robotic perception. No prior industry experience required.

Option B (Master’s Path) : Master’s degree in Computer Science, Electrical Engineering, Biomedical Engineering, or related technical discipline, paired with 2 to 5 years of hands‑on industry experience building and maintaining computer vision or deep learning systems in production.

Deep Learning Frameworks: Advanced proficiency in Python and PyTorch.

Computer Vision Fundamentals: Solid grounding in geometric vision, multi‑view geometry, optical flow, and image processing libraries (OpenCV).

Engineering Standards: Demonstrated experience writing clean, maintainable, version‑controlled code (Git, Docker, CI/CD pipelines, unit testing).

Problem‑Solving: Proven ability to navigate ambiguous visual challenges, whether demonstrated through first‑author peer‑reviewed publications or successful commercial software deliverables.

Preferred Qualifications

Knowledge of surgical AI challenges and state of the art.

Prior experience with endoscopic, laparoscopic, or medical imaging benchmarks (e.g., EndoVis, Cholec80).

Working knowledge of modern C++ for algorithm acceleration and edge integration.

Familiarity with inference optimization frameworks (NVIDIA TensorRT, ONNX, OpenVINO).

Experience with LLMs and/or multimodal models training.

Experience with scene 3D reconstructions methods from 2D images, such as SfM, 3DGS or NeRF.

Experience with monocular visual SLAM methods.

Experience with soft tissue deformation models (FEM, PBD, XPBD).

Basic understanding of regulated medical device software standards (IEC 62304, ISO 14971).

Key Abilities

Analytical mind and rigor. The candidate must be responsible and reliable.

Ability to work in a multidisciplinary environment.

Autonomy and adaptability. The candidate must be proactive, curious, and resourceful.

Excellent written and verbal communication skills in French and English.

Candidate Profiles: What Success Looks Like

Ph.D. (Fresh Graduate)

Deep theoretical knowledge of cutting‑edge architectures.

Independence in navigating unmapped research problems.

Proven rigor with commercial software lifecycles.

Cross‑functional collaboration with product/embedded teams.

Experience balancing model complexity against latency, memory, and runtime budgets.

Why Join Us

Be part of a passionate and dynamic team working at the forefront of medical innovation.

Contribute to the development of products with a significant social and technological impact.

Opportunities for rapid career growth in a fast‑growing startup.

Stimulating and collaborative work environment.