# Member of Technical Staff, Robotics Engineer at Runway Ml > Onsite · United States · Staff · Software engineering · open. Source: https://alderhq.app/jobs/ashby%3Arunway-ml%3A0f1c42db-8bbf-4e69-a17c-b6f45244605d (read 2026-11-14). ## Facts (observed) - Company: [Runway Ml](https://alderhq.app/companies/runway-ml) - Location text: New York, NY - Where it can be done from (inferred): Onsite · United States (evidence: "Location: New York, NY") - Posted: 2026-06-02 (166 days ago) - First seen by alder: 2026-11-02 · last verified: 2026-11-12 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/runway-ml/0f1c42db-8bbf-4e69-a17c-b6f45244605d ## Pay and sponsorship - Posted pay: $270k–$370k per year (from the listing's pay field) - Market band for similar posted roles (New York, n 346): p25 $200k, median $230k, p75 $264k ## Description (the employer's text) 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. \*Titles posted to our careers page are updated regularly to best advertise the role and expected seniority, but internally we have a flat titling system with two types of titles: one for individual contributors and one for people managers. ### 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 Robotics Engineer to bring our video-native foundation models onto real hardware: deploying world-model-based policies on real robots and making them work in the real world. You will work across the full stack of robot learning — from data collection and task design, to policy deployment, to physical evaluation. 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. ### What you’ll do Own the deployment loop for learned policies (VLAs, diffusion policies, World Action Models) on real robot arms: inference serving, action decoding, controller integration, latency budgets, and safety limits Diagnose real-world policy failures — determining whether the problem is data coverage, camera/proprioception mismatch, or execution — and partner with the research team to fix it at the right layer Design demonstration data collection protocols (task setup, camera placement, teleop conventions) that produce data our world models can actually learn from — working with our existing teleop and lab infrastructure Partner with research to run controlled experiments connecting world model representations, data composition, and fine-tuning recipes to physical success rates Define and run physical evaluation protocols so results are trustworthy and comparable across policy iterations Adapt our policy recipe to partner hardware and new embodiments ### What you’ll need You have personally deployed software on real robot hardware and iterated to make it work — whether learned policies, motion planning, classical control, or perception-driven manipulation. You can walk through a specific system you shipped, what broke on the physical robot that didn't break in sim or testing, and how you fixed it. Fluency in the software-to-robot interface: action/command spaces, control frequencies, observation pipelines, calibration, and how each affects real-world behavior Comfort working at the intersection of software and physical systems: you can reconfigure a robot workspace and trace a policy failure in the same afternoon Bonus: direct experience deploying learned policies (VLAs, diffusion policies) on real hardware; experience with video/multimodal generative models or world models 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. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Arunway-ml%3A0f1c42db-8bbf-4e69-a17c-b6f45244605d and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.