The opportunity
As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the…
What you'll do
Develop monitoring techniques and observability methods that track AI: behavior in real time to identify and flag deviations, emergent capabilities, or anomalous outputs;
Research mechanisms for layered control, including fail-safes, oversight: protocols, and intervention methods that can halt or redirect AI systems when risks are detected;
Design red-team simulations to probe weaknesses in oversight and control: mechanisms, and build mitigations to close identified gaps;
Collaborate with policymakers, engineers, and other researchers to establish: standards and benchmarks for AI monitoring and escalation.
Commitment to our mission of promoting safe, secure, and trustworthy AI: deployments in the industry as frontier AI capabilities continue to advance.
Practical experience conducting technical research collaboratively. You: should be comfortable designing control and monitoring experiments for AI systems, building prototype systems, and quickly turning new ideas from the research literature into working prototypes.
What they're looking for
- A track record of published research in machine learning, particularly in generative AI.
- At least three years of experience addressing sophisticated ML problems,: whether in a research setting or in product development.
- Strong written and verbal communication skills to operate in a cross-functional team.
- Experience with runtime monitoring, anomaly detection, or observability for ML systems.
