VLA Pretraining Lead: Shape Robotic Intelligence at Scale

VLA Pretraining Lead: Shape Robotic Intelligence at Scale

Full-Time 80000 - 100000 Β£ / year (est.) No working from home possible
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At a Glance

  • Tasks: Lead the pretraining of our VLA framework for robotic intelligence across platforms.
  • Company: Join Humanoid, a pioneering company in robotics and AI.
  • Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
  • Other info: Be part of a dynamic team driving innovation in robotics.
  • Why this job: Shape the future of robotics and make a significant impact on technology.
  • Qualifications: Experience in machine learning and strong leadership skills required.

The predicted salary is between 80000 - 100000 Β£ per year.

Humanoid seeks a Pretraining VLA Lead to own the pretraining stage of our VLM/VLA framework powering a fleet of robots across platforms.

Define base model strategy, data mixtures, and scaling, leading research engineers training foundation policies on diverse real-world and synthetic data.

You will design large-scale distributed training, establish evaluation suites, and collaborate with MLOps and Data Platform teams to ensure smooth transfer to post-training and real-robot inference.

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VLA Pretraining Lead: Shape Robotic Intelligence at Scale employer: Thehumanoid

Thehumanoid is an exceptional employer that prioritises employee well-being and professional growth, offering a dynamic work culture in vibrant locations like London, Boston, and Vancouver. With competitive equity, over 30 days of time off, and comprehensive private healthcare, we empower our team to thrive both personally and professionally while leading innovative supply chain solutions.

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Contact Details:

Thehumanoid Recruitment Team

We think you need these skills to ace VLA Pretraining Lead: Shape Robotic Intelligence at Scale

Model Strategy Definition
Data Mixture Design
Scaling Techniques
Large-Scale Distributed Training
Evaluation Suite Establishment
Collaboration with MLOps
Collaboration with Data Platform Teams