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We’re looking for a curious and motivated Reinforcement Learning Intern to help advance the next generation of decision-making systems for autonomous driving. In this role, you’ll work embedded in a research team to develop scalable RL algorithms that enable vehicles to learn complex behaviors directly from experience — both in simulation and the real world.
Job Responsibility:
Help advance the next generation of decision-making systems for autonomous driving
Work embedded in a research team to develop scalable RL algorithms that enable vehicles to learn complex behaviors directly from experience — both in simulation and the real world
Requirements:
Currently pursuing a PhD or Masters in Computer Science, Robotics, Electrical Engineering, or a related field, with a focus on Machine Learning, AI, or Computer Vision
Experience in research in Reinforcement Learning
Interest in one or more: synthetic data, representation learning, and Offline RL
Comfortable working in Python and libraries like PyTorch, NumPy, and Pandas
A principled mindset: you enjoy brainstorming, making assumptions, building, testing, and iterating on ideas to see what works
Nice to have:
Experience collaborating on research projects or contributing to shared codebases
Publications or submissions at venues such as CVPR, ICCV, CoRL, NeurIPS, ICML, ICRA, or RSS are a nice bonus, but not required
What we offer:
Competitive compensation and benefits
A dynamic and fast-paced work environment in which you will grow every day - learning on the job, from the a diverse team of the brightest researchers and engineers in this space
A culture that is ego-free, respectful and welcoming
Potential to publish your research work at a top flight conference
The chance to be part of a truly mission driven organisation and an opportunity to shape the future of autonomous driving
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