RESEARCH ENGINEER -
REINFORCEMENT LEARNING, SIMULATION, ROBOTICS

At Latent we strive to reinvent how games are made using cutting-edge AI. We are currently building the next generation, real-time and physics-based animation technology for virtual worlds, which we believe has the potential to transform the industry. To get there, we are solving some of the most interesting and beautiful problems in the field.

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You are a junior to staff level research engineer who knows machine learning techniques inside out and has experience in reinforcement learning techniques for character/robot movement in simulated environments — names like Peng, Levine, Finn or Abeel are quite familiar to you. You also have experience in developing algorithms in simulated environments, such as Isaac Sim/Lab.

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You can instantly crawl your way inside Pytorch code and Python libraries, understand them, and optimize them. You intuitively understand research papers about new generative and reinforcement learning methods while having a sight put on implementation.

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Also, you pride yourself in being a bit of a generalist, you are curious and capable to learn about anything and you are capable of working indepently.

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If you don't fit perfectly in this description, but you are driven and you think you can learn what it takes, then we would love to hear from you as well.