AI Engineer - Reinforcement Learning (Senior)

What you’ll be doing
Develop cutting-edge reinforcement learning algorithms to enable robots to autonomously execute motor commands based on raw sensor input. Design, test, and refine your algorithms to meet the demands of complex real-world locomotion, autonomy and manipulation tasks. Collaborate with the computer vision and imitation learning team to innovate methods that leverage both simulated and real-world data. Implement deployment-ready code for the real robot, optimized for the robot’s computational constraints. Build, lead and mentor an exceptional team of software engineers. Provide expert guidance to product managers and executives for strategic decision-making. Create and maintain documentation, guidelines, and best practices to streamline knowledge sharing.
What you must have
Master’s degree or higher in a relevant field such as Engineering, Robotics, or Machine Learning. A minimum of five years of industry or research experience, with PhD experience applicable. Strong deep learning fundamentals, including supervised and self-supervised learning techniques, and reinforcement learning, including Markov Decision Processes (MDPs), neural network architectures, policy optimization algorithms, model-based vs. model-free RL, exploration-exploitation strategies, value function methods, transfer learning, domain adaptation, sim-to-real transfer, etc. Strong background in robotics including autonomy and/or manipulation. Experience with deploying artificial neural networks on hardware platforms. Ability to write production-level code in modern C++. Ability to prototype algorithms and train deep neural networks in Python.
Get some bonus points
PhD degree in Robotics, Engineering, Computer Science, Machine Learning or a similar discipline, or an equivalent amount of research experience. Publications at top-tier conferences. Experience in managing a software team.

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