AI Engineer - Reinforcement Learning (Senior)
Team: Embodied AI
Location: Zürich
Commitment: Full-Time
Workplace Type: onsite
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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