Research Engineer, Data Foundations

Reposted 10 Hours Ago
Hiring Remotely in USA
Remote
270K-370K Annually
Mid level
Artificial Intelligence • Computer Vision • Machine Learning • Software
An applied AI research company building for the next frontier of intelligence and human creativity
The Role
Design and curate multimodal, multitask datasets and run controlled training experiments to evaluate how data composition affects world-model performance. Build large-scale synthetic data pipelines, filtering and quality-control systems. Define benchmarks and evaluations, and partner with product and creative teams to translate target behaviors into data strategies that enable simulation-driven AI capabilities.
Summary Generated by Built In

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.

About the role

Building general world models — systems that understand and simulate reality across tasks, modalities, and domains — demands training data that is as rich and varied as the real world itself. We’re looking for Research Engineers to own the data behind our models: what they learn from, how well they learn it, and what new capabilities that unlocks. You will design datasets, run modeling experiments, and build the infrastructure to generate and curate data at scale — directly shaping what our models can do, with applications ranging from creative tools to robotics.

What you'll do
  • Design multimodal, multitask datasets that teach world models new capabilities — deciding what data to collect, generate, or curate and measuring its effect on model behavior

  • Run controlled training experiments to understand how data composition drives model performance across tasks and domains

  • Build and operate large-scale pipelines for synthetic data generation, filtering, and quality control

  • Define evaluations and benchmarks that measure whether our models are actually improving at the things that matter

  • Partner with product and creative teams to translate target behaviors and capabilities into concrete data strategies

What you'll need
  • 4+ years of experience in machine learning, bonus points for data-centric approaches

  • Experience with large multimodal datasets and generative models (video, image, or multimodal)

  • Deep intuition for how data composition and quality translate to model capabilities

  • Comfort working across the full research stack: data analysis, dataset creation, model training, evaluation, and back again

  • Proficiency with at least one ML framework (e.g. PyTorch, JAX) and distributed compute tools (e.g. Ray, Kubernetes)

  • Excitement about building AI that simulates the world

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.

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

  • Universal World Simulator

  • GWM-1

  • Gen-4.5

  • General World Models

  • Robotics SDK

  • Conversational Real-time Agents

  • Runway Studios

We're excited to be recognized as a best place to work:

Crain's | InHerSight | BuiltIn NYC | INC

Skills Required

  • 4+ years of experience in machine learning
  • Experience with large multimodal datasets and generative models (video, image, or multimodal)
  • Deep intuition for how data composition and quality translate to model capabilities
  • Comfort working across the full research stack: data analysis, dataset creation, model training, evaluation
  • Proficiency with at least one ML framework (e.g. PyTorch, JAX)
  • Experience with distributed compute tools (e.g. Ray, Kubernetes)
  • Data-centric approaches (bonus points)
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The Company
HQ: New York, NY
185 Employees
Year Founded: 2018

What We Do

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.

Why Work With Us

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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