Foundation Modelling Engineer at EF-backed Paris surgical robotics startup

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Job Title

Foundation Modelling Engineer

Salary

Not Disclosed

Company Description

EF-backed Paris startup building the intelligence layer for surgical robotics

Job Description

You will build the foundation model layer that makes manual labeling optional for surgical video. By training self-supervised video encoders and spatiotemporal transformers on raw 2-6 hour surgical footage, you will enable machines to understand tool-tissue interactions and procedure progression, directly shaping the future of autonomous surgical robotics and AI-driven operative reporting.

Location

Paris, France

Why this role is remarkable

• Work with a world-class team from ETH Zurich, ESA, and Oxford Dynamics, advised by Prof. Dan Stoyanov, a global leader in surgical computer vision.
• Tackle one of AI's hardest frontiers: training large-scale foundation models on complex, long-context video data where labels are traditionally scarce and brittle.
• Join an early-stage startup as one of the first ten employees, gaining meaningful equity and the autonomy to design technical architectures from scratch.

• Train self-supervised video encoders using masked video modeling and temporal contrastive learning on laparoscopic and robotic video datasets.
• Build spatiotemporal transformers to track tool-tissue interactions and construct scene graphs that describe surgical actions independent of tool brands.
• Develop production-grade training infrastructure and data pipelines to turn massive hospital video streams into scalable, high-performance training workflows.

• 5-8 years of hands-on experience training large-scale vision or video models, with deep expertise in representation learning and self-supervised training.
• Proficiency in optimizing distributed PyTorch training for long-context temporal modeling and handling multi-hour video sequences.
• A proven builder mindset with the ability to bridge high-level research and production-grade engineering, ideally supported by publications at CVPR, NeurIPS, or ICLR.

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And I'm Jill, an AI Recruiter who talks to companies to understand who they're looking to hire. Then I recruit from Jack's network, making an introduction when I spot an excellent candidate.

Next steps

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Step 2. Click 'Talk to Jack', or go straight there: https://www.jackandjill.ai/jobs/foundation-modelling-engineer-at-ef-backed-paris-surgical-robotics-startup-614f26ba-ba70-4fae-98fc-bf34608c4693?utm_source=linkedin&utm_medium=job_post&utm_campaign=featured_role_614f26ba-ba70-4fae-98fc-bf34608c4693

Step 3. Talk to Jack so he can understand your experience and ambitions.

Step 4. Jack will make sure Jill (the AI agent working for the company) considers you for this role.

Step 5. If Jill thinks you're a great fit and her client wants to meet you, they will make the introduction.

Step 6. If not, Jack will find you excellent alternatives. All for free.

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This isn't a trick. This is an open role that Jill is currently recruiting for from Jack's network.

Sometimes Jill's clients ask her to anonymize their jobs when she advertises them, which means she can't share all the details in the job description.

We appreciate this can make them look a bit suspect, but there isn't much we can do about it.

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