AI Research Scientist (£120k-£200k + Equity) at Paddington Robotics Limited

Location:
London, United Kingdom
Salary:
120000.00 – 200000.00
Type:
Permanent
Main Industry:
Search Information Technology Jobs
Job ID:
133090301
Company:
Jack & Jill/External ATS
Posted On:
15 June 2026

Job Title

AI Research Scientist

Salary

£120k-£200k + Equity

Company Description

Paddington Robotics Limited – VC-backed applied AI robotics lab

Job Description

Join an elite team led by a Magic Pony co founder to build physical AI for the chaotic real world. Moving beyond lab simulations, you will leverage high-quality data from actual robot deployments to develop generalisable models for manipulation and navigation, delivering immediate commercial impact while solving fundamental challenges in robotics.

Location

London, UK
Why this role is remarkable Work under Zehan Wang, co-founder of Magic Pony (acquired by Twitter for $150M), alongside a world class team from Amazon AGI, InstaDeep, and top tier universities. Eschew traditional lab only research for an “iterative deployment” approach, testing your models on real hardware in human centric environments like supermarkets to capture unique edge cases. Enjoy significant ownership and early stage equity in the UK’s leading applied AI robotics team, backed by proven founders and preparing for an upcoming funding round. What you will do Develop and scale 3D perception and data capture systems to help robots understand and navigate unpredictable, dynamic human environments safely. Design and implement cutting edge robot learning approaches, including Vision Language Action (VLA) models and Reinforcement Learning for complex manipulation tasks. Prototype, ship, and iterate on code that runs on physical hardware, bridging the gap between theoretical research and robust real world robotic performance. The ideal candidate Holds a PhD or equivalent with 5+ years of experience publishing at top tier venues such as ICRA, CoRL, NeurIPS, or CVPR. Demonstrates a proven track record of deploying cutting edge AI models onto physical hardware, showing resilience against sensor noise and environmental mess. Possesses strong engineering fundamentals to prototype and ship code independently while maintaining a low ego, highly collaborative approach to rapid iterative development.

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