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Scale AI

Research Scientist, AI Safety and Alignment

San Francisco, California, United States +1

Location
San Francisco, California, United States · New York, United States
Work
Not stated
Employment
Not stated
Level
Not stated
Function
Data & AI
Pay
$259.2K – $324K a year
Posted
7 months ago

Pay and the market here

The top of this role’s range, $324K a year, is 25% above the median of $260K for data jobs in San Francisco (middle half $220K – $325K, 1,098 jobs that state pay).

1,323 data jobs open in San Francisco: 11% remote, 283 posted in the last 30 days.

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About the role

Scale Labs, Research Scientist — AI Safety and Alignment

As the leading data and evaluation partner for frontier AI companies, Scale plays a central role in understanding and safeguarding AI systems. Building on this expertise, Scale Labs has launched a new team focused on technical AI safety and policy research, to bridge the gap between frontier AI research and policy, helping policymakers make informed, evidence-based decisions about AI capabilities and risks.

Our research tackles some of the hardest open problems in AI safety: assessing the alignment of frontier models, developing control protocols and monitoring methods, preserving the monitorability, understanding failure modes in multi-agent systems and recursive self-improvement. We collaborate closely with partners across industry, the public sector, and academia and regularly publish our findings. We are looking for talented researchers to join us in shaping this vision.

As a Research Scientist on this team, you will conduct research and build evaluations, tools, and datasets that help us understand and reduce risks from frontier AI systems. For example, you might do any or all of the following:

  • Design and stress-test control protocols and monitoring systems that detect and limit unsafe behavior by AI models and agents in deployment;
  • Build alignment evaluations that probe for deception, sabotage, scheming, reward hacking, and other misaligned behaviors;
  • Study monitorability, including whether a model’s reasoning stays faithful and legible enough to supervise, and how training methods and deployment practices can preserve or erode it;
  • Investigate risks that emerge when multiple AI agents interact, such as collusion, coordination failures and steerability;
  • Develop threat models and evaluations for AI systems that automate AI research and development, to track progress toward recursive self-improvement and inform preparedness planning;
  • Work with government agencies and other labs to scope and design evaluations that measure and mitigate risks from advanced AI;
  • Publish research and evaluation methodologies, and write technical reports for policymakers.

Ideally you’d have

  • Commitment to our mission of promoting safe, secure, and trustworthy AI as capabilities continue to advance.
  • Practical experience conducting technical research collaboratively. You should be comfortable building and instrumenting ML pipelines, building evaluation harnesses, running experiments on frontier models and agents, and quickly turning new ideas from the research literature into working prototypes.
  • Familiarity with current research in at least one of the areas above.
  • A track record of published research in machine learning, particularly in AI safety and alignment.
  • At least three years of experience working on sophisticated ML problems, in research or product development.
  • Strong written and verbal communication skills, including the ability to explain technical findings to policymakers and work across functions.

Nice to have

  • Experience designing evaluations and benchmarks, or building tools and pipelines to analyze model and agent trajectories at scale.
  • Experience with red-teaming or adversarial testing of AI systems, including stress-testing safeguards such as monitors and control protocols.
  • Familiarity with AI safety policy and governance frameworks (e.g., NIST AI RMF, EU AI Act, Korea AI Basic Act, frontier AI safety frameworks).

Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions. If you’re excited about advancing AI safety and contributing to our mission, we encourage you to apply, even if your experience doesn’t perfectly align with every requirement.

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; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

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:

$259,200—$324,000 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us

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.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

Source

Posted by Scale AI on their own hiring page, job-boards.greenhouse.io. OptiTalent shows it as published, read 07 Nov 2026 10:41 UTC; the original is the reference.

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