Head of AI

Dex; Greater London; Sur place; GBP 150 000 - 230 000; Plein temps

Résumé du poste

Dex is partnering to build a surgical AI platform that unites computer vision, segmentation, and vision-language-action for real-time robotic guidance. You will lead the AI pillar end‑to‑end, from prototype to production, and own data pipelines, federated learning, and collaboration with the simulation team.

This leadership role requires building and mentoring a small team and delivering clinically relevant models with sub-20ms latency on edge hardware.

Qualifications

• Experience shipping production AI/ML models in computer vision or related fields.
• Familiarity with medical imaging data formats and segmentation networks.
• Proven ability to meet real-time latency constraints and deploy to edge devices.
• Hands-on with MLOps, distributed training, and federated learning.

Responsabilités

• Lead end-to-end AI pillar from prototype to production in neurosurgical domain.
• Architect data pipelines for kinematics and tissue-interaction data across endpoints.
• Own federated learning stack and privacy-preserving model improvements.
• Collaborate with simulation teams on Isaac Sim and sim-to-real transfer.
• Grow and manage a team of 2–3 engineers around the AI pillar.

Connaissances

Production AI/ML models

Computer vision/segmentation

Vision-language models

Medical imaging (DICOM MONAI)

Real-time inference (sub-20ms)

MLOps / DGX/RTX infrastructure

Federated learning

Leadership (2–3 engineers)

London-based / in-person

Outils

NVIDIA FLARE

Isaac Sim

Edge hardware (NVIDIA AGX)

Description du poste

This role is with one of Dex's trusted partner companies. We work closely with their teams to truly understand their culture, goals, and what they're looking for, so we can match you with the right opportunity and give you context about the role before you commit to a process.

Dex is an AI recruiter agent that helps you run your job search. Tell Dex your stack, seniority, and what you want to build. We will manage your applications and surface other opportunities that are a fit.

The role

Forget incremental improvements. This company is building the surgical intelligence layer, a platform that combines computer vision, AI, and augmented reality to give surgeons and robots real-time 3D navigation. Their core differentiator: a surgical foundation model, trained on kinematics, tissue interactions, and surgeon intent captured across deployed endpoints. This isn't academic research; it's about shipping models that fundamentally change surgical outcomes.

This isn't a research role. You'll lead the AI pillar end-to-end, building a team from the ground up. Your mandate: ship production AI. That means delivering an anatomy recognition model for neurosurgery (prototype by Q2 2028, ≥85% accuracy), then evolving the foundation model from computer vision to vision-language-action for device automation. You'll architect the data pipeline, own the federated learning stack, and define the boundary with the simulation team on synthetic data and sim-to-real transfer. Models in research are interesting; models in the operating room are valuable.

The work

• Deliver a working prototype of the anatomy recognition model for neurosurgery by Q2 2028, hitting ≥85% segmentation accuracy.
• Lead the surgical foundation model program: from computer vision and segmentation, to vision-language, to vision-language-action models for device automation.
• Architect the data pipeline for kinematics and tissue-interaction data across all deployed endpoints.
• Own the federated learning stack, deploying NVIDIA FLARE for privacy-preserving model improvement.
• Define the boundary and partner with the simulation team on Isaac Sim, synthetic data, and sim-to-real transfer.

What You Bring

• You've shipped production AI/ML models. Computer vision, segmentation, or vision-language experience is ideal.
• Experience with medical imaging (DICOM, segmentation networks, MONAI) or a rapid ability to ramp into it.
• You've worked with real-time inference constraints: sub-20ms latency, deployment to edge hardware like NVIDIA AGX.
• You own DGX/RTX-class training infrastructure and MLOps. Federated learning experience is a strong plus.
• You've led at least 2-3 engineers and want to grow a full AI pillar.
• Based in or around London, or able to work in person 3+ days a week.

Why apply through Dex

This is a rare leadership role at the cutting edge of surgical AI, the kind that's often hard to find and oversubscribed. We filter out the noise so you can focus on what matters.

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