Senior Embodied AI Engineer - Controls
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At a glance
Job overview
AIM Intelligent Machines is hiring a Senior Embodied AI Engineer - Controls. AIM Intelligent Machines is building autonomous AI-powered fleets for heavy machinery in mining, construction, and defense operations. They seek a Senior Embodied AI Engineer to develop and validate advanced control and learning algorithms for robotic systems. This role involves designing experiments, combining classical and learning-based control methods, and collaborating with other engineers to integrate AI control stacks into production platforms.
Key focus areas include Automate, Develop, implement, and validate advanced control and learning algorithms for real-world embodied robotic systems, Design and conduct experiments to expand control robustness, precision, and adaptability across diverse tasks and environments, and Combine classical and learning-based control methods (e.g., MPC, IL, RL) for scalable and reliable skill acquisition.
Successful candidates bring 5+ Years Industry Experience, Production-Level Robotic Control Experience, and Strong Foundation In Modern Control Techniques. Important skills include Automate Advanced Control And Learning Algorithms, Design Experiments, Conduct Experiments, Control Robustness, Control Precision, and Control Adaptability.
Skills & qualifications
Skills
Qualifications
Full job description
About AIM Everything humanity depends on is mined, dug, or grown. At AIM, we are building the autonomous linchpin of civilization. We transform heavy machinery—bulldozers, loaders, excavators—into AI-powered fleets that operate continuously, safely, and at peak performance in the world’s harshest environments.
AIM runs production mines, large scale infrastructure builds, and defense operations as a TRL9 hardened system, not a science experiment.
Built by engineers from mining, construction, Waymo, SpaceX, Google and Tesla, AIM enables scalable earthmoving, turbocharging the global economy’s physical foundation. AIM is backed by some of the most sophisticated capital in the world, including General Catalyst, Khosla Ventures, Elad Gil, Human Capital, Ironspring Ventures, Mantis, DCVC.
Responsibilities
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Automate, Develop, implement, and validate advanced control and learning algorithms for real-world embodied robotic systems.
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Design and conduct experiments to expand control robustness, precision, and adaptability across diverse tasks and environments.
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Combine classical and learning-based control methods (e.g., MPC, IL, RL) for scalable and reliable skill acquisition.
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Collaborate with perception and systems engineers to integrate AI control stacks into production platforms.
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Leverage simulation, digital twins, and expert demonstrations to accelerate control policy development and deployment.
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Stay up-to-date on cutting-edge research in control theory, reinforcement learning, and embodied AI.
Qualifications
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5+ years industry experience
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Proven experience delivering production-level robotic control systems in real-world deployments (e.g., autonomous vehicles, manipulators, humanoid or mobile robots).
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Strong foundation in modern control techniques (e.g., MPC, adaptive control, system identification) and their integration with learning-based methods.
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Deep understanding of reinforcement learning, imitation learning, and optimization for dynamic systems.
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Proficiency in Python and familiarity with C++ for real-time robotics applications.
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Experience working with high-fidelity simulators (e.g., Isaac Sim, Omniverse, Mujoco) for control development and testing.
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Excellent communication and teamwork skills, with the ability to bridge between AI research and robotic systems engineering.
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