Reinforcement Learning Algorithms Engineer
Mid
Shifters is looking for a Reinforcement Learning Algorithms Engineer to develop and deploy advanced whole-body control policies for our autonomous quadruped robots. You will train robust behaviors for dynamic locomotion, balance, recovery, manipulation, and coordinated loco-manipulation tasks using large-scale physics simulation. The role includes reward and curriculum design, motion imitation, sim-to-real transfer, and close collaboration with robotics, mechatronics, and embedded teams to validate policies on real hardware.
Requirements
- Strong Python programming skills.
- Practical experience with reinforcement learning, including policy-gradient methods such as PPO.
- Experience developing, training, and evaluating algorithms in simulation.
- Strong problem-solving skills and the ability to work independently and as part of a multidisciplinary team.
- Experience with computer vision, ROS 2, robotics, or embedded computing platforms is an advantage.
- Experience deploying algorithms on physical robotic systems is a strong advantage.
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