Research Engineer, Data Foundations

🕒 July 28

🇺🇸 United States – Remote

💵 $270k - $370k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 19%

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Logo of Runway

Runway

51 - 200 employees

Founded 2018

🤖 Artificial Intelligence

☁️ SaaS

📱 Media

Artificial Intelligence • SaaS • Media

Runway is a company building foundational "Real-World Intelligence" — large models and systems that can understand, simulate and act in the visual world. It offers three main product platforms built on these models: Runway Creative, an all‑in‑one cloud creative suite for generating and editing video, images and audio for individuals and teams; Runway Dev, an AI media platform and API for developers to run models, compose pipelines and trigger workflows; and Runway Robotics, a toolkit for photorealistic simulation, policy inference and synthetic data generation powered by their General World Model (GWM-1). Runway also publishes research (e. g. , GWM-1, Gen-4. 5 video model) and serves both individual creators and enterprise customers.

📋 Description

• 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

🎯 Requirements

• 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

🏖️ Benefits

• Health insurance • 401(k) • Flexible work arrangements • Paid time off

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