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.