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The Machine Learning Researcher will design datasets and evaluate environments for agentic systems, focusing on data quality and benchmarking model performance in RL settings. They will collaborate with teams to translate workflows into evaluative frameworks and improve the understanding of high-quality datasets.

Build benchmarks and eval infrastructure for real-world AI evaluation. Partner with researchers and customers to design benchmarks, process multimodal data, build data pipelines, sandboxed execution environments, storage, and orchestration. Ship iterative eval infrastructure and own engineering for customer engagements.

Build and ship end-to-end features for internal dashboard and customer portal in a TypeScript/Next.js stack. Design UIs, implement APIs, data models, tests, media playback, embedding-based search, secure access controls, and work with large multimodal datasets across Postgres and AWS.

Own and grow a small portfolio (2-4) of strategic foundation-lab and frontier AI accounts. Build multi-year deal strategies, map stakeholders, coordinate internal teams (DataLab, Solutions, Legal, CSM), and drive significant GMV through structured agreements, accurate forecasting, and expansion opportunities. Represent Protege at events and surface account-derived insights to shape product and supply strategy.