Applied Research Lead, Reinforcement Learning
Overview
Runway is building AI to simulate the world through merging art and science. They believe that world models are at the frontier of progress in artificial intelligence.
Job Description
Runway is focused on creating AI models that experience the world and learn from their mistakes, similar to humans. They aim to change how stories are told, how scientific progress is made, and how the next frontiers of humanity are reached.
Responsibilities
- - Lead efforts in applying reinforcement learning based techniques
- - Improve the quality and controllability of the models that power Runway''s research and tools
Required Skills
- - 4+ years of relevant engineering or research experience in applying reinforcement learning
- - Very strong programming skills and ability to write clean and maintainable research code
- - Deep interest in building human-in-the-loop systems for creativity
- - Passion for seeing research through from initial conception to eventual application
- - Experience mentoring and teaching other researchers
- - Strong communication, collaboration, and documentation skills
Benefits
- - Competitive salary based on market rates
- - Commitment to pay equity
- - Opportunity to work with a diverse and exceptional team
About the company
Runway builds AI to simulate the world by merging art and science. Runway believes that world models represent the frontier of progress in artificial intelligence. Language models alone are insufficient to solve the world’s hardest problems—such as robotics, disease, and scientific discovery. Meaningful progress requires models that can experience the world and learn from their mistakes, in much the same way humans do. Runway focuses on accelerating this learning through simulation rather than real-world trial and error. By enabling rapid experimentation in simulated environments, world models provide a clear path toward general-purpose simulation and more capable AI systems. Runway operates offices in New York, San Francisco, Seattle, London, and Tel Aviv, with team members working remotely from around the world.
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