Member of Technical Staff, Research Tooling & Data Platform

About the role 

We're looking for an engineer to own Runway's internal exploratory data analysis (EDA) and evaluation platform used daily by our ML research, design, product, and creative teams. This is a high-impact role where you'll directly accelerate research velocity and enable better decision-making across the company.

This platform helps researchers query large-scale datasets, run evaluations on model outputs, and analyze results - all through an intuitive interface. As the owner, you'll be responsible for the full product experience: from database query optimization and infrastructure management to building user-facing features that make complex ML workflows accessible to non-engineers.

A peek at our technical stack

Our API endpoints for real-time collaboration and media asset management is written in TypeScript, and runs in ECS containers on AWS Fargate. We leverage multiple AWS-native components, such as S3, CloudFront, Lambda, Kinesis, and SQS, as building blocks of our infrastructure.

Our inference backend is written in Python (PyTorch, TorchScript), and is deployed across multiple clusters / cloud providers. We use Kubernetes for container orchestration, and k8s-native components such as Flyte, Kueue, and Kyverno efficient job orchestration. We invest in prometheus and grafana for monitoring, and Terraform to manage our infrastructure.

What you’ll do 

• Own the EDA platform end-to-end: Take full ownership of architecture, infrastructure, feature development, and operations
• Optimize for scale: Improve query performance and write efficiency for vector search, integrate with new data warehouses, and optimize our custom query parsing/suggestion system
• Build for researchers: Design and ship features that help ML researchers source data faster, run more effective evaluations, and iterate quickly
• Enable cross-functional users: Work with design, product, and creative teams to build intuitive evaluation workflows
• Manage infrastructure: Deploy and maintain services across ECS and Kubernetes, including embedding services and database integrations
• Provide support: Be responsive to user needs, debug issues quickly, and gather feedback to prioritize improvements

What you’ll need

• 4+ years of industry experience in a backend focused software engineering role
• Strong experience in at least 2 of 3 areas (platform/infrastructure, ML domain knowledge, frontend/product engineering) with eagerness to learn the third:
  1. Platform/infrastructure: experience with vector databases, cloud primitives (i.e. SQS, ECR, Kinesis) and container orchestration (Kubernetes, ECS)
  2. ML domain knowledge: Understanding of ML workflows, model training, evaluation, testing, dataset management, feature engineering, or research tooling
  3. Product engineering: Ability to build clean, intuitive user experiences with product thinking and user empathy. You care deeply about building tools people love to use (TypeScript/React experience is a plus)
• Comfortable setting up and maintaining production infrastructure and services
• Self-starter who can navigate ambiguity and make pragmatic technical decisions
• Humility and open mindedness; at Runway we love to learn from one another

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