Research Scientist Intern, Reinforcement Learning
Is this job for you?
Build my CV Build your CV and see how well you match this role — and every other one.
The role
Develop scalable reinforcement learning algorithms for autonomous driving, enabling vehicles to learn complex behaviors from experience in simulation and the real world.
Focus areas include reinforcement learning, imitation learning, offline RL, and world modelling, with emphasis on temporal credit assignment and policy optimization.
Design, implement, and evaluate algorithms, and translate research findings into deployable solutions.
Collaborate with cross-disciplinary teams and contribute to shared codebases, prioritizing reproducibility and potential publications.
Proficient in Python and libraries such as PyTorch, NumPy, and Pandas, with a principled, iterative approach to experimentation.
Ideal candidates are pursuing a Master’s or PhD in ML, AI, CS, or robotics, with hands-on RL research and a passion for embodied AI challenges.
Focus areas include reinforcement learning, imitation learning, offline RL, and world modelling, with emphasis on temporal credit assignment and policy optimization.
Design, implement, and evaluate algorithms, and translate research findings into deployable solutions.
Collaborate with cross-disciplinary teams and contribute to shared codebases, prioritizing reproducibility and potential publications.
Proficient in Python and libraries such as PyTorch, NumPy, and Pandas, with a principled, iterative approach to experimentation.
Ideal candidates are pursuing a Master’s or PhD in ML, AI, CS, or robotics, with hands-on RL research and a passion for embodied AI challenges.
See the full job post
Responsibilities, requirements, skills and benefits — create your free account.
or
Already have an account?
Log inYou might also like these jobs
No closely matching jobs yet — here are the most recent ones.