Research Engineer - Robot Learning
Role details
Job location
Tech stack
Job description
We are hiring Research engineer in Robot Learning to design the next generation of few-shot, data-efficient imitation learning algorithms powering our robots. Your work will define how Bleu Robotics teaches robots new industrial tasks - and how fast, from how little data, and how reliably.
The central research challenge is data efficiency: learning useful, generalizing behaviors from a handful of demonstrations, not thousands. Hitting our one-hour demonstration-to-deployment target depends directly on the algorithms you will design. This is a frontier research problem with immediate, measurable industrial impact: every gain in sample efficiency translates into a faster, broader, and more useful product.
This is a research role focused on shipping algorithms into a real product. We are an early-stage company and do not publish at this stage. You will work in close collaboration with the Vision & Perception and Integration teams to ensure the methods you develop run on real robots, in real factories., * Design, prototype, and evaluate few-shot imitation learning algorithms, with a primary focus on data efficiency
- Advance our internal state of the art in imitation learning, policy learning, and representation learning for control
- Run rigorous experiments on real robots and contribute to the data, evaluation, and infrastructure needed to do so
- Translate research prototypes into algorithms robust enough to ship as part of our product
- Collaborate with the Vision & Perception and Integration teams to move research from prototype to production
- Help shape the long-term research agenda of the company
Requirements
- PhD or MSc in robotics, machine learning, or a closely related field, from a leading research lab
- Track record of published research at top venues such as ICRA, IROS, CoRL, NeurIPS, ICML, RSS, or equivalent
- Demonstrated research expertise in imitation learning, learning from demonstration, or policy learning for robots - ideally with a focus on data efficiency or few-shot learning
- Strong Python skills and fluency with PyTorch
- Hands-on experience training, evaluating, and debugging learning systems on real robots (not solely simulation)
- Professional proficiency in English (internal working language), The strongest candidates will combine deep research expertise with experience across several of the following:
- Few-shot learning or meta-learning for control
- Representation learning for embodied agents
- Learning on humanoid robots or other complex high-DoF platforms
- Postdoctoral experience, or research positions in industry labs or top academic groups
- A history of translating research into deployed systems
- Familiarity with ROS 2 and standard robotics infrastructure
Benefits & conditions
- A clear, ambitious research mission with measurable real-world impact
- A diverse fleet of advanced robots, including humanoids, on which to run your research
- Research that ships: your algorithms run on real machines in real factories
- Tight collaboration with engineering teams that take your work to production
- Significant ownership of the research agenda as an early member of the team
- A focused, technically strong team and a serious engineering culture
- English-speaking working environment, no French required
- Fair compensation + equity