Senior AI Product Manager, Cybersecurity

Навыки

• Code review
• Коммуникация
• Data Quality
• Форензика и реагирование
• Google Tag Manager
• Лидерство
• Machine Learning

О компании и продукте

• At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
• We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
• We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.
• We comply with the United States Department of Labor's Pay Transparency provision .

Задачи

• 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
• 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
• Ideally, You'd Have
• Real cybersecurity work under your belt, rather than security-adjacent product experience: vulnerability research, fuzzing and crash triage, reproducer development, patch and root-cause analysis, exploit development, malware analysis, red teaming, detection engineering, or incident response
• Competitive CTF, published CVEs, a bug bounty record, or OSS-Fuzz contributions all count
• 5+ years in product management, technical program management, consulting, or customer-facing technical roles — or equivalent depth as a practitioner with a clear pull toward product ownership
• A working view of the AI-for-security evaluation landscape and where it falls short: CyberGym, Cybench, CVE-Bench, BountyBench, CyberSecEval
• CyberGym sets the bar we hold ourselves to — real vulnerabilities sourced at scale, execution-grounded verification, and tasks hard enough that frontier agents still clear only about a fifth of them
• Enough software engineering depth to read unfamiliar code, reason about runtime behavior, and hold your own with senior engineers and ML researchers
• Familiarity with how models are post-trained and evaluated, including agentic scaffolds and container-based rollout infrastructure
• Sound judgment on dual-use questions, and genuine care about building capability measurement that helps defenders more than attackers
• Entrepreneurial mindset, bias for action, and comfort operating in fast-moving, ambiguous environments
• Please reference the job posting's subtitle for where this position will be located
• For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is

Требования

• Excellent stakeholder management and executive communication skills, with a demonstrated ability to drive alignment across cross-functional organizations

Условия

• Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale
• 205,600 — $257,000 USD

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