Scale AI
Machine Learning Research Lead, Security & Policy Research Lab
Scale AI, New York, New York, us, 10261
Overview
Scale is seeking a highly experienced, thoughtful, and mission-driven research lead to drive the Scale AI Security and Policy Research Lab (SPRL). The team aims to bridge the gap between AI researchers and global policymakers to make informed, scientific decisions about AI risks and capabilities. SPRL conducts research on agent robustness, AI control protocols, and AI risk evaluations, generating data and insights to inform benchmarking and evaluations for AI models and systems, with a focus on secure, responsible, and innovative AI governance globally. The team collaborates across industry, the public sector, and academia and regularly publishes findings. SPRL’s research addresses frontier safety science for AI models and works at the leading edge of frontier risk evaluations, agent robustness, and AI controls. Current research includes designing and building harnesses to test AI models for dangerous capabilities, uplift research related to potentially dangerous AI-enabled uplift, developing AI-assisted evaluation pipelines, and collaborating with policymakers, engineers, and researchers to establish standards and benchmarks for AI monitoring and escalation. Responsibilities
Lead a team of research scientists and engineers on foundational AI safety and security work in evaluation and robustness. Drive research initiatives on frameworks and benchmarks for frontier AI models, spanning reasoning, coding, multi-modal, and agentic behaviors. Design and advance scalable oversight methods, leveraging model-assisted evaluation, rubric-guided judgments, and recursive oversight. Collaborate with leading research labs across industry and academia. Publish research at top-tier venues and contribute to open-source benchmarking initiatives. Remain deeply engaged with the research community, understanding trends and helping set them. Qualifications
Track record of impactful research in machine learning, especially in generative AI, evaluation, or oversight. Significant experience leading ML research in academia or industry. Strong written and verbal communication skills for cross-functional collaboration. Experience building and mentoring teams of research scientists and engineers. Publications at major ML/AI conferences (e.g. NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR) and/or journals. Additional Information
Our research interviews assess practical ML prototyping and debugging, understanding of research concepts, and alignment with Scale’s culture. We do not ask LeetCode-style questions. Note: The following compensation and benefits information is provided for transparency and is subject to location and eligibility. Base salary range for this full-time role in San Francisco, New York, and Seattle is $240,000 – $340,000 USD. Compensation includes base salary, equity, and benefits. Compensation packages for eligible roles include base salary, equity, and benefits. The salary range displayed reflects the minimum and maximum target for new hire salaries, determined by work location, skills, experience, and education. Equity grants are subject to Board approval. Recruiters can share location-specific details during hiring. Benefits include comprehensive health, dental, and vision coverage, retirement benefits, a learning and development stipend, generous PTO, and potential commuter benefits where applicable. EEO and Accessibility
Scale is committed to equal employment opportunity regardless of race, color, religion, sex, national origin, sexual orientation, gender identity, age, disability status, veteran status, or other protected characteristics. We provide reasonable accommodations in the application process and throughout employment as needed. If you require accommodations, please contact accommodations@scale.com. Please note: We collect and use personal data for recruitment purposes in accordance with our privacy policy.
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Scale is seeking a highly experienced, thoughtful, and mission-driven research lead to drive the Scale AI Security and Policy Research Lab (SPRL). The team aims to bridge the gap between AI researchers and global policymakers to make informed, scientific decisions about AI risks and capabilities. SPRL conducts research on agent robustness, AI control protocols, and AI risk evaluations, generating data and insights to inform benchmarking and evaluations for AI models and systems, with a focus on secure, responsible, and innovative AI governance globally. The team collaborates across industry, the public sector, and academia and regularly publishes findings. SPRL’s research addresses frontier safety science for AI models and works at the leading edge of frontier risk evaluations, agent robustness, and AI controls. Current research includes designing and building harnesses to test AI models for dangerous capabilities, uplift research related to potentially dangerous AI-enabled uplift, developing AI-assisted evaluation pipelines, and collaborating with policymakers, engineers, and researchers to establish standards and benchmarks for AI monitoring and escalation. Responsibilities
Lead a team of research scientists and engineers on foundational AI safety and security work in evaluation and robustness. Drive research initiatives on frameworks and benchmarks for frontier AI models, spanning reasoning, coding, multi-modal, and agentic behaviors. Design and advance scalable oversight methods, leveraging model-assisted evaluation, rubric-guided judgments, and recursive oversight. Collaborate with leading research labs across industry and academia. Publish research at top-tier venues and contribute to open-source benchmarking initiatives. Remain deeply engaged with the research community, understanding trends and helping set them. Qualifications
Track record of impactful research in machine learning, especially in generative AI, evaluation, or oversight. Significant experience leading ML research in academia or industry. Strong written and verbal communication skills for cross-functional collaboration. Experience building and mentoring teams of research scientists and engineers. Publications at major ML/AI conferences (e.g. NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR) and/or journals. Additional Information
Our research interviews assess practical ML prototyping and debugging, understanding of research concepts, and alignment with Scale’s culture. We do not ask LeetCode-style questions. Note: The following compensation and benefits information is provided for transparency and is subject to location and eligibility. Base salary range for this full-time role in San Francisco, New York, and Seattle is $240,000 – $340,000 USD. Compensation includes base salary, equity, and benefits. Compensation packages for eligible roles include base salary, equity, and benefits. The salary range displayed reflects the minimum and maximum target for new hire salaries, determined by work location, skills, experience, and education. Equity grants are subject to Board approval. Recruiters can share location-specific details during hiring. Benefits include comprehensive health, dental, and vision coverage, retirement benefits, a learning and development stipend, generous PTO, and potential commuter benefits where applicable. EEO and Accessibility
Scale is committed to equal employment opportunity regardless of race, color, religion, sex, national origin, sexual orientation, gender identity, age, disability status, veteran status, or other protected characteristics. We provide reasonable accommodations in the application process and throughout employment as needed. If you require accommodations, please contact accommodations@scale.com. Please note: We collect and use personal data for recruitment purposes in accordance with our privacy policy.
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