Applied AI Engineer |Robotics | Physical Systems|

about the company Our client is an innovative technology lab operating at the cutting edge of advanced automation and applied artificial intelligence. They are developing next-generation intelligent systems designed to transform physical labor on a massive scale. This is a highly dynamic environment where rapid iteration is prioritized, allowing engineers to see their software directly drive real-world physical capabilities within days. about the role You will serve as a critical engineer at the intersection of machine learning and physical execution. Your core focus will be translating complex AI models into tangible, real-world actions. Design and train sophisticated machine learning policies for dynamic, real-world control systems. Conduct hands-on experiments to systematically debug and close the gap between simulated environments and physical reality. Build and maintain high-speed data pipelines and simulation environments that enable rapid iteration. Analyze system performance during deployments to drive continuous improvements back into the training loop. Collaborate closely with cross-functional engineering teams to integrate software with complex physical constraints. skills and experience Proven experience in applied machine learning, specifically focusing on reinforcement or imitation learning. Demonstrated ability to deploy models onto actual physical systems, moving beyond theoretical simulations. Advanced proficiency in Python and familiarity with modern ML or physics-based frameworks. A highly empirical, debugging-oriented mindset with a focus on practical results that work in the real world. Bonus: A background in control theory, dynamics, or experience with domain adaptation and multi-axis physical systems. To apply online please use the 'apply' function, alternatively you may contact Evangeline.(EA: 94C3609/ R24124002 )