Member of Technical Staff, ML Platform

🕒 September 22

🇺🇸 United States – Remote

💵 $240k - $290k / year

⏰ Full Time

🔴 Lead

🖥 Software Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Runway

WebsiteLinkedInAll Job Openings

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

• Own the evaluation platform end to end, including tooling and systems to generate, annotate, review, and adapt evaluations at frontier scale • Define CLIs, APIs, GUIs, and storage layers for a seamless, fast, sophisticated, and collaborative evaluation process • Work with research teams on video, image, audio, agents, and robotics to understand measurement needs and build platform capabilities • Set standards for model evaluation, including reproducibility, metric definitions, reporting formats, and trust thresholds for action • Support platform adoption and integration across training, production model serving, and other research efforts • Contribute to ML Platform tools and systems used to train and serve frontier models • Design and build systems that generate samples at scale, score them with automated metrics and human annotations, track results across checkpoints and releases, and deliver findings to researchers quickly • Define operationally what constitutes a better model and how results become ship/no-ship decisions

🎯 Requirements

• 5+ years of experience building ML infrastructure or data platforms in production environments • Experience with evaluation, experimentation, or benchmarking systems • Strong Python and PyTorch skills • Hands-on experience running large batch GPU workloads on Kubernetes • Experience designing data pipelines and storage for large volumes of media or model outputs • Attention to versioning and reproducibility • Familiarity with experimental statistics, including paired comparisons, confidence intervals, multiple-comparison pitfalls, and inter-rater agreement • Experience building internal tools end to end, from command line to browser • Ability to lead a broad technical area, gather requirements, set direction, make tradeoffs, and drive a roadmap • Familiarity with the full model development lifecycle: data, training, evaluation, and serving • Strong systems thinking and pragmatic approach to production reliability • Self-starter able to work embedded with research teams and move fast • Humility and open mindedness • Nice to have: track record building evaluation suites for generative models • Nice to have: hands-on work with LLM- or VLM-as-judge pipelines • Nice to have: experience with online experimentation platforms and connecting offline metrics to product outcomes • Nice to have: prior work evaluating agents or robotics policies

🏖️ Benefits

• Access to best-in-class models, agents, GPUs, storage and cloud services • Broad access to the latest models and harnesses • Diverse and inclusive workplace with equal opportunity to succeed • Salary is part of the overall compensation package • Pay equity commitment