2 Positions: Machine Learning Engineer & Machine Learning Researcher

Candidates should take the time to read all the elements of this job advert carefully Please make your application promptly. My client is a scaling robotics start-up that is creating autonomous industrial robots capable of handling intricate, dexterous tasks. They're looking for Senior ML Engineers who want the freedom to bridge the gap between state-of-the-art research in embodied AI and real-world systems. You'll be joining a team of accomplished roboticists with excellent PhDs, high-impact research, and industrial know-how, who will help nurture and develop you to the next level! Salary: Up to £150k Location: London Onsite: Most days What You’ll Be Doing (Machine Learning Engineer): Implement and scale state-of-the-art AI algorithms to be deployed on real-world robotic systems Build robust data pipelines and work with multi-modal sensor data Collaborate with a talented team of researchers to improve and refine algorithms for real-world tasks Ensure the scalability and maintainability of production systems, with a strong focus on (low-level) MLOps What You’ll Be Doing (Machine Learning Researcher): Conduct groundbreaking research to develop new algorithms and models for robotics Work on advanced learning approaches such as reinforcement learning and imitation learning Contribute to creating multi-robot systems and cross-embodiment learning techniques Drive innovation by publishing research and attending top conferences Engineer Background: Expertise in PyTorch or TensorFlow, distributed computing, and multi-GPU training Robotics experience, particularly in reinforcement/ imitation learning Experience in cloud infrastructure (AWS, GCP, or Azure) and containerization Ability to translate research papers into deployable systems Researcher Background: PhD or advanced degree in Robotics, Machine Learning, or a similar field Experience with top-tier conferences like CoRL, ICRA, RSS, ICML, ICLR, NeurIPS Strong knowledge of reinforcement learning, imitation learning, and real-world deployment