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About the Role

The VLA Core team builds the base vision-language-action model that the entire manipulation pipeline depends on. This involves deep learning at scale, training models from scratch on multi-embodiment trajectory corpora and internet-scale video, with real deployment constraints. The model must fit and run on a real robot. This is a senior individual contributor role with no management track, focused on research-adjacent output for real robots.

Responsibilities

Pre-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 to specify data requirements, identify failure modes, and 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 for ingesting synthetic data and teleop logs, versioning them, applying weak-supervision labelling, curating balanced datasets, and automatically surfacing fresh failure cases into retraining.
Work with MLOps and Data Platform teams to scale distributed training and optimize models for real-time edge inference on the robot.
Design and train multimodal, action-conditioned world models (video, state, action and language) using diffusion-based and transformer architectures.
Build video prediction and dynamics models that stay physically consistent over long horizons, including contact-rich manipulation, serving as pretrained priors for VLA policies.
Develop learned-simulator evaluation to score candidate policies offline, predict real-world success rates before deployment, and roll out policy futures for safety review and planning.
Generate synthetic rollouts and counterfactual experience (rare events, cross-platform and sim-to-real transfer) and measure their effect on downstream task performance.
Build data pipelines that turn fleet telemetry, teleoperation logs, and internet-scale video into training corpora.
Run scaling and ablation studies on architecture, data mixture, and context length.

Requirements

3+ years building deep learning systems in industry or research, with shipped models or published work.
Deep hands-on experience with at least one of: LLMs, VLMs, image or video generative models (architecture, training and inference).
For the World Models track: diffusion models, autoregressive transformers, latent-variable models, or video prediction.
Experience training models yourself: pre-training runs, distributed infrastructure.
Experience with deep learning infrastructure: streaming datasets, checkpointing and state management, distributed training strategies, debugging numerics and training instabilities.
Strong Python and PyTorch or JAX.
Strong coding fundamentals.
Empirical rigor: careful evaluations, honest baselines, clear experiment docs, crisp communication of trade-offs.
Proactive: ability to take an open, messy problem and drive it without waiting for a spec.
Working English.

Skills

LLMs
VLMs
Image generative models
Video generative models
Diffusion models
Autoregressive transformers
Latent-variable models
Video prediction
Python
PyTorch
JAX
Deep learning infrastructure
Distributed training
MLOps
Data Platform

Location

London, UK

Work Type

On-site
Full-time

Experience Level

Senior

Salary/Compensations

A wide range, set by the level you show in the interviews.

Benefits

Equity: stock options with meaningful upside.
30+ paid days off: 23 days annual leave, all UK bank holidays and a company shutdown between Christmas and New Year.
Private healthcare: fully funded, including virtual and in-person care.
Pension: 8% total contribution (5% employee, 3% employer) on full earnings.
Daily food: free breakfast, catered lunch and snacks in the office.
Real ownership: direct access to founding leadership, real input on product direction and room to drive key initiatives from day one.
Visa sponsorship and relocation to London.

About the Company

Humanoid is building the world’s most capable, commercially scalable and safe humanoid robots.
Its platform, HMND-01, is already deployed in real industrial environments, making 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.