Scientist/Researcher | Robotics | Embodied AI | Humanoid

Take embodied AI out of the lab and into the real world.Building the future of open-source robotics!

about the company

Our client isn't just writing research papers. They are an applied R&D lab actively building the advanced, open-source robotic platforms of the future. Their core mission is making scalable, automated physical labor an economic reality. To do this, they move fast across hardware, autonomy, and simulation to get real machines doing real work in unstructured environments. If you want to be at the exact intersection where cutting-edge software meets complex physical hardware, this is where it happens.

about the role

We're looking for someone who wants to give robots the ability to truly understand and navigate their physical surroundings. You won't just be tweaking algorithms in a vacuum; you'll be designing representation models for whole-body control and pushing the boundaries of predictive world models. Most importantly, you will be getting your hands dirty: deploying and stress-testing your perception and learning algorithms directly on physical hardware to ensure robust behaviors outside of a controlled lab setting. You'll also stay deeply plugged into the latest AI breakthroughs and actively contribute back to the open-source community.

skills and experience

• Deep roots in computer vision, specifically with a track record of wrestling with uncurated, messy, real-world visual data.
• Hands-on expertise in representation learning and self-supervised training methods.
• You know what it takes to own a model end-to-end: from building the data pipelines and debugging, to running rigorous physical evaluations.
• Battle scars from sim-to-real transfer: you've actively migrated models from simulation and made them work on moving physical hardware.
• High proficiency in Python or C++, alongside strong familiarity with modern robotic simulation environments.
• A solid grasp of the broader ML ecosystem, including how Large Language Models (LLMs) are shaping embodied AI.
• Bonus points: Direct experience with imitation learning, real-time control on embedded systems, or contact-rich manipulation (the hard stuff!) will make you a major standout.

To apply online please use the apply function, alternatively you may contact Evangeline. (EA: 94C3609/ R24124002)