Staff ML Research Scientist

4 weeks ago


Vancouver BC, Canada Harnham Full time €200,000 - €300,000

Staff Research Scientist – Robotics & Machine Learning Location: Vancouver (Hybrid – at least 2 days onsite) Compensation: $200–300k base + equity A pioneering robotics and AI team is hiring a Staff Research Scientist to push the boundaries of embodied intelligence. In this role, you’ll work end to end across research, simulation, and real-world deployment, developing ML-driven control systems for dexterous humanoid robots. You’ll shape the direction of reinforcement and imitation learning research, design scalable training and data pipelines, run large-scale simulation experiments, and bring cutting-edge algorithms onto robots equipped with advanced sensing capabilities. This is a rare opportunity to contribute research that transitions directly into physical, real-world performance. What You’ll Do Develop and advance RL/IL algorithms for complex manipulation tasks Lead high-impact research directions and guide experimentation strategy Design training and data-collection systems that speed up deployment Improve efficiency, reliability, scalability, and compute performance of learning systems Run experiments in simulation and on real robots, debugging end to end Diagnose failures and design robust, production-ready solutions Collaborate closely with ML researchers, robotics engineers, and applied teams What We’re Looking For PhD in ML, Robotics, Computer Science, Applied Math, or equivalent expertise 5+ years building and deploying robotic manipulation systems (simulation + real robots)5+ years hands-on experience with RL/IL for real-world robotics 4+ years developing large-scale parallel simulation pipelines Strong background in continual learning and sim-to-real transfer Experience transitioning ML research into production robotic systems Publication record in top-tier robotics/AI venues (ICRA, IROS, CoRL) Technical Strengths Expert Python Proficiency with PyTorch or TensorFlow Experience with ROS2 and parallel compute (CUDA, OpenMP) Deep understanding of RL theory and practical implementation



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