Senior Full-Stack Engineer, Physical AI

London Engineering / Full time / On-site About us Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production. Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more. We're an ambitious team of 100+ working at the frontier of AI and have raised $60M in Series C funding from Wellington Management, CRV, Next47 and Y Combinator. The role We're building tools for the full Physical AI data stack — from data acquisition, through ingestion and curation at scale, to 3D rendering, annotation, and verification. You'll solve problems of large-scale efficient data transfer and storage, complex domain modelling, applying the latest machine learning models, and squeezing performance out of web browsers. You'll work with the biggest names in robotics and autonomous vehicles, and join a small, highly collaborative team at a crucial stage of accelerated development. You'll be a key driver of progress on a core part of our product, operating with a high degree of autonomy and crafting performant, reliable, and maintainable solutions at speed.

What you'll do

Build and maintain high-performance frontend experiences, including rendering complex 3D scenes with thousands of objects at smooth frame rates
Work across the full stack — from backend data pipelines and storage systems to frontend visualisation and interaction
Take end-to-end ownership of projects, from product and architectural decisions through to deployment, monitoring, and measuring user impact
Work with visual, spatial, and sensor data to make sense of the physical world
Tackle complex domains at massive scale using simple, well-crafted solutions
Take initiative, be proactive in problem-solving, and continuously seek improvements

Who we're looking for

Experienced: you've seen a lot and built a lot — personally developed and maintained multiple systems from scratch, with a deep understanding of the trade-offs involved in building reliable...