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.
We're looking for a Data Engineer to build and scale the data infrastructure that powers Runway's AI research and business intelligence. You'll own critical data pipelines spanning production databases, analytics warehouses, and large-scale ML training datasets. This role sits at the intersection of data engineering, ML infrastructure, and analytics—you'll enable both world-class research and data-driven business decisions.
You'll work on challenging problems at scale: managing billions of rows of multimodal training data, building CDC streams from production systems, optimizing vector databases for ML workflows, and creating the foundational data layer that the entire company relies on.
Our data infrastructure spans multiple specialized systems: LanceDB for vector storage and dataset versioning with multimodal training data, ClickHouse as our analytics warehouse receiving CDC streams from production Postgres via AWS Kinesis, and BigQuery for training run logs and evaluation results. We use Ray for large-scale distributed data processing on managed Kubernetes clusters, handling preprocessing, feature generation, and dataset curation at scale.
We're actively building out our data platform—introducing dbt for standardized transformations, improving dataset versioning and data lineage tracking, scaling data sourcing pipelines, and establishing better data quality practices. We use Prometheus and Grafana for monitoring, and Terraform for infrastructure management. This is an opportunity to bring best practices and technical leadership as we mature our data infrastructure to support rapidly growing ML training and research needs.
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: $240,000-290,000
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.
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