Deep Learning Engineer

3 Days Old

About the Role
In this role, you will work on all aspects of training capable manipulation policies, be it pre-training of a base policy on a diverse multi-embodiment corpus of manipulation trajectories, fine-tuning models to perform a specific task well, curating data collection processes or exploring productive ways to use synthetic data. This is primarily a deep learning-focused role, so we are looking for experience solving real problems using
modern neural networks, and experience in robotics isn't strictly required. However if you don't have such experience, be prepared that you'd need to familiarize yourself with a new domain quickly.
What You'll Do
Train policies via representation learning, behaviour cloning and RL; own the full loop from data to deployment.
Partner with teleoperations to drive data collection: specify what "good" looks like,ensure diversity/coverage, and close the gap between sim and real.
Run pre-/mid-/post-training on multimodal LLM/VLM/VLA stacks; plug in new modalities (vision, audio, proprioception, LiDAR/point clouds, …) without breaking existing ones.
Build and maintain continuous pipelines: ingest simulation + tele-op logs, version them, apply weak-supervision labelling, curate balanced datasets, andauto-surface fresh failure cases into retraining.
Work with MLOps & Data Platform teams to scale distributed training and optimize models for real-time edge - M...
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Location:
London
Salary:
£100,000 - £140,000 /annum
Job Type:
FullTime
Category:
Engineering

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