Member of Technical Staff, Robotics Research Engineer

About the role

* Open to candidates based near our NYC office or those willing to relocate. Building general world models - systems that understand and simulate reality across tasks, modalities, and domains - requires closing the loop between learned representations and real-world action. We're looking for a Research Engineer to own the robotics vertical of our world models: taking our video-native foundation models and turning them into policies that control real robots in the real world. You will work across the full stack of robot learning - from data collection and task design, to policy training, to physical evaluation and deployment. This is a hands-on, execution-oriented role at the intersection of foundation models, learned robot policies, and hardware. You'll bring deep robotics domain expertise and help us ship world-model-based robot policies end-to-end, with applications ranging from manipulation to mobile robotics.

Responsibilities

• Design and execute end-to-end robot learning pipelines - from task design and demonstration data collection through policy training, and physical evaluation
• Deploy and iterate on learned policies (VLAs, diffusion policies, World Action Models) on real robot hardware, closing the loop between model predictions and physical outcomes
• Run controlled experiments to understand how world model representations, data composition, and fine-tuning strategies translate to downstream manipulation and locomotion performance
• Build and maintain physical evaluation benchmarks and infrastructure - designing tasks, procuring hardware, calibrating systems, and measuring real-world success rates
• Coordinate robot data collection efforts across internal teams and external partners, ensuring data quality, coverage, and consistency across embodiments
• Partner with the world model research team to translate model capabilities into concrete robotics applications, identifying where our video foundation models unlock new robot behaviors
• Identify and resolve bottlenecks across the robotics stack - whether in data, training infrastructure, hardware configuration, or evaluation methodology - to keep the overall system moving fast

Requirements

• Hands-on robotics experience spanning data collection, model training, and physical evaluation. Direct experience with modern learned policies (e.g., VLAs, diffusion policies) on real hardware.
• Experience with robot data collection, teleoperation, and demonstration pipelines across at least one manipulation or mobile platform
• Strong intuition for the full robot learning lifecycle: task design → data collection → policy training → physical evaluation
• Comfort working across software, hardware, and physical systems - you can debug a training run and reconfigure a robot workspace in the same afternoon
• Proficiency with at least one ML framework (e.g., PyTorch, JAX)
• Bonus: experience with video or multimodal generative models, world models, or using foundation model representations for downstream control
• Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide.
• Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates.
• Working at Runway
• Great things come from

Benefits

Additional Information

We are building AI to simulate the world through merging art and science. We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won't solve the world's hardest problems - robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world. World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached. Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you.

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