• Partner with downstream AI application teams to define shared evaluations that codify application expectations of LLMs and other foundation models, ensuring progress can be transparently tracked against real-world needs. • Design rigorous benchmarks and evaluation methodologies across ranking & recommendations, content understanding, and language/text generation — grounded in a deep technical understanding of LLMs, their strengths, limitations, and failure modes. • Lead the development of evaluators and strong baselines to ensure in-house LLMs and other foundation models demonstrate clear advantages over off-the-shelf alternatives. • Build scalable, reproducible data and evaluation systems that make dataset creation and evaluation design as nimble and experiment-friendly as model development itself. • Hire, grow, and nurture a world-class team, fostering an inclusive, high-performing culture that balances research innovation with engineering excellence. • Work closely with the teams developing Netflix’s foundation models (including our core LLM) to ensure evaluation and data insights are folded back into the cadence of model development. • Proactively influence the ML Platform and Data Engineering teams at key interfaces.