Bleu Robotics is an AI company developing universal AI software for the deployment of advanced robots , humanoids, mobile manipulators, and industrial arms, in real factories. The convergence of humanoid robotics and modern AI is one of the most significant technical opportunities of the decade, and most of the work today still happens in research settings. We are building the software layer required to bring it into operational use.
We have a strong ambition to become the next Microsoft to run on every industrial humanoid. We have closed our pre-seed round with Top-tier fund to deploy our robot in Tier 1 manufacturing facilities.
We are looking for deeply passionate scientists who can help us push the frontier and build a major lab in our physical AI.
To enable a robot to learn a new industrial task from a few demonstrations and operate autonomously, with under one hour between the start of the demonstration and the start of deployment.
This objective shapes our roadmap and every technical decision we make.
The roleWe 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 We are an early-stage company and do not publish at this stage.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
The engineering team is organized around three focus areas with multiple contributors each: Integration, Vision & Perception, and Robot Learning (this role). Early hires will help shape the research agenda, engineering practices, hiring, and culture.
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
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
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