The opportunity
Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles.
What you'll do
Own the roadmap and strategy for Scale's Cybersecurity portfolio across: training data, RL environments, agentic task suites, and evaluation products — and stand the product line up end to end, from task taxonomy and sourcing through pricing and first external release.
Define the capability map we train and measure against: vulnerability discovery, proof-of-concept reproduction, patch generation and regression safety, secure code review, supply-chain analysis, malware and binary analysis, detection engineering, and incident triage.
Make the strategic call on where Scale competes across the offense–defense: spectrum — which capabilities we build training data for, which we only measure, and which we decline.
Partner with ML researchers and security practitioners on task: specifications, grader design, and verifiable rewards, holding to execution-grounded verification wherever possible: a task counts as solved only when the reproducer fires or the patch holds without breaking functionality.
Drive the infrastructure roadmap: reproducible vulnerability images, fuzzing and build toolchains, sandboxed execution, network-segmented ranges, automated verification — and build sourcing pipelines that scale past hand-curation.
Own the responsible-development posture: containment, coordinated disclosure for live vulnerabilities surfaced during task construction, need-to-know handling of sensitive artifacts, and customer vetting, working with Security, Legal, and Policy to make these processes real rather than nominal.
What they're looking for
- Establish governance for data quality, contamination prevention, license and: IP hygiene, reproducibility, and release management.
- Recruit and steward a contributor network of working practitioners: vulnerability researchers, exploit developers, malware analysts, detection engineers, incident responders — and design quality controls that hold up when reviewers are validating work at the edge of their own expertise.
- Own external partnerships across open-source benchmark collaborations,: academic security groups, and enterprise data partnerships.
- Work directly with frontier labs and enterprise customers to understand where: their models fail on security work, translate that into roadmap, and partner with GTM on launches and thought leadership.
