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Runway

Applied Research Lead, Reinforcement Learning

Posted 6 Days Ago
Be an Early Applicant
Remote
Hiring Remotely in USA
280K-380K
Senior level
Remote
Hiring Remotely in USA
280K-380K
Senior level
Lead efforts in applying reinforcement learning techniques to improve models at a global AI research company, mentoring others, and building human-in-the-loop systems for creative tasks.
The summary above was generated by AI

We are a global AI research and technology company focused on building Universal Simulation systems. The research we are doing and the tools we are building are maturing rapidly and are quickly becoming the foundation for how we will all soon approach making anything. From images to videos, scripted media to documentaries, graphic design to architecture, interactive games to social media, new forms of learning and the future of entertainment itself. Everyone will be empowered to make anything. There will no longer be any barriers to entry.

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.

About the role

*Open to hiring remote across North America and Europe — we also have offices in NYC, San Francisco, Seattle, London, and Tel Aviv

We’re looking for a Sr. Applied Research Scientist to lead efforts in applying reinforcement learning based techniques to improve the quality and controllability of the models that power Runway’s research and tools. This role is for someone who has a strong background building impactful and novel machine learning projects, has strong software engineering skills, and is deeply interested in seeing their research materialize in novel user interfaces for creative tasks.

What you’ll need
  • 4+ years of relevant engineering or research experience in applying reinforcement learning to align language, image, and/or video generation models
  • 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

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.

There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range.

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.

Salary range: $280,000-$380,000 

Working at Runway

Great things come from great teams. We’d love to hear from you.

We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply.

More about Runway

  • Runway Research
  • Runway's AI Film Festival
  • Creative Dialogues Series
  • Runway Studios
  • Our Behaviors and Company Mission

We're excited to be recognized as a best place to work Crain's | InHerSight | BuiltIn NYC | INC


Top Skills

Machine Learning
Reinforcement Learning
Software Engineering

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