Deployed Researcher, Strategic Deployment

The Strategic Deployment team makes frontier models more capable, reliable, and aligned to transform strategically-important domains. On one hand, this involves deploying models in real-world, high-stakes settings to drive AI-driven transformation and elicit insights—training data, evaluation methods, and techniques—to shape our frontier model development. On the other hand, we leverage these learnings to build the science and engineering of impactful frontier model deployment.

Put differently, we want to understand: if AGI is viewed as AI being able to majorly transform our economy, how close are we to AGI? What’s still missing? How do we bridge these gaps?

About the Role

As a Deployed Researcher on the Strategic Deployment team, you’ll conduct hands-on research and engineering to adapt and evaluate frontier models in real-world, high-impact environments. Your work will drive transformational impact and generate critical insights into model behavior, capability limits, and the interventions needed for a successful AI deployment.

This role is based in San Francisco, CA. We follow a hybrid model (3 days/week in-office) and offer relocation support.

In this role, you will:

• Harness frontier models to drive real-world, high-impact tasks and surface key capability gaps.

• Build evaluations, training data, and infrastructure to support safe, robust deployments.

• Conduct research that spans large language model reinforcement learning and fine-tuning, science of evaluations, and data selection—with an emphasis on steering model behavior, improving generalization, and ensuring reliability.

• Work with internal teams and external partners to scope and execute custom frontier model deployments.

• Care about real-world impact of AI.

• Are excited to drive how frontier models are developed and deployed.

• Have hands-on experience in AI research, systems, or applied science (e.g. RL, fine-tuning, evals).

• Have strong engineering skills, particularly in designing, deploying and optimizing large-scale AI systems.

• Are excited by ambiguous, open-ended problem spaces with high impact and stakes.

• Enjoy working in open-ended problem spaces and high-feedback environments.