Role: VLA Pre-training Engineer / Deep Learning Engineer – World Models (2 openings)Company: HumanoidLocation: London, UK (King’s Cross) – on-site, five days a weekJob Type: Full-timeAbout HumanoidHumanoid is building the world’s most capable, commercially scalable and safe humanoid robots.
Its platform, HMND-01, is already deployed in real industrial environments, which makes Humanoid the most serious humanoid robotics company in Europe.
300+ people, 34+ nationalities, flat structure: your decisions ship directly into real robots.
Offices in London (HQ, King’s Cross), Boston, Vancouver and San Diego.
Values: Speed, Ambition, Passion, Trust.
This is deep learning at scale: training models from scratch on multi-embodiment trajectory corpora and internet-scale video, with real deployment constraints.
The model has to fit and run on a real robot.
Robotics experience is not required.
If you come from LLMs, VLMs or video generation, be ready to get up to speed on a new domain quickly.
This is a senior individual contributor role with no management track.
The team is research-adjacent, but the output is models that run on robots.
Results are shared as blog posts, not papers.
There are two tracks in one team.
They are the same role with a different focus, so you can lean into either.
Track 1: VLA Pre-trainingPre-train base models on a diverse multi-embodiment corpus of trajectories, fine-tune policies to excel at specific tasks and explore synthetic data.
Post-train policies with behaviour cloning and RL, and own the full loop from data to deployment.
Partner with the Data Collection team: specify what good data looks like, identify failure modes, ensure diversity and coverage.
Run pre-, mid- and post-training on the VLA stack; explore new modalities and architecture changes.
Build and maintain continuous pipelines: ingest synthetic data and teleop logs, ve.