Machine Learning Engineer
Robotics ML Engineer | Our client is an early-stage company building the infrastructure that teaches machines to act in the physical world. They gather real-world experience and run on-device reinforcement learning to turn it into robot capability, with the aim of taking repetitive physical labour off people. The team is made up of researchers and engineers from top universities and leading AI labs, and it’s growing.
The role:
They fine-tune LLMs so that they can operate robots, and the models have to run in real time. They need a Robotics ML Engineer who trains these models and understands what they’re doing when they fail on real hardware. This is a model-training role, not a general ML role and not a robotics infrastructure role. The people who do it well know both how to train a model and how a robot behaves.
What you’ll do:
- Fine-tune and post-train LLMs and VLA (vision-language-action) models for real-time robotic control
- Run post-training experiments and evaluate foundation models on robotics tasks
- Debug model behaviour on robots, working out why a model does what it does and whether the cause is the model, the environment or the setup
- Work with researchers and founders to turn training results into reliable robot capability, comparing simulation with real-robot evaluation
- What they’re looking for
- Hands-on experience training or post-training models.
- Proficient with robotics and embodied AI.Experience with VLA models, world models or world action models is ideal. LLM experience, and RL applied to robotics, are also very relevant
- Strong Python and engineering fundamentals
- Careful experimental judgment: you can say whether an improvement is real and what the evidence doesn’t show
- Recent graduates with substantial research or project work are welcome. A Master’s or PhD is preferred