VC-backed Robotics Startup | London (on-site, with flexibility)
Compensation: Up to £220k + equity package
About
This is a VC-backed robotics company building the intelligence layer for industrial machines — forklifts, cranes, excavators and other heavy equipment. The approach is pragmatic: start with remote teleoperation to generate real‑world operator data at scale, then train Vision‑Language‑Action models toward increasing autonomy.
The teleoperation system is live and generating data. The autonomy stack is being built on top of it now. The near‑term approach is imitation learning on open VLA foundations, adapted to proprietary operator data. RL follows once the baseline is proven.
This is a founding hire to lead the research efforts, working alongside the CTO and CEO — setting technical direction, owning the model stack, and hiring a team of 6–7 over the coming months.
What you’ll do
- Own the model stack end‑to‑end — architecture, training, evaluation, and iteration
- Adapt and fine‑tune open VLA foundations on proprietary operator data from live teleoperation
- Define and execute the near‑term AI roadmap, starting with imitation learning
- Build toward RL‑based methods once the imitation learning baseline is validated
- Translate research ideas into production‑ready systems running on physical machines
- Set technical direction for the AI team and hire into it as the company scales
- Work directly with the CTO on strategy, roadmap, and team structure
What you’ll need
- Strong background in robotics, embodied AI, or physical autonomy
- Hands‑on RL experience — applied to real systems, not just simulation
- Experience building or fine‑tuning foundation models at scale (ideally VLA‑style architectures)
- Track record deploying models in real‑world environments, not just benchmarks
- Comfortable operating as a player‑coach: technically hands‑on, capable of leading a team
- Applied research focus — you deliver to production, not papers
- Background at a robotics lab, autonomous vehicle company, or embodied AI team
Shortlisted candidates will be contacted within 48 hours.
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