Protege is the trusted source for AI-ready, real world data and expertise at every stage of the AI lifecycle. Backed by a16z and CRV.
About the role
We are building Protege to solve the biggest unmet need in AI — getting access to the right training data. The process today is time intensive, incredibly expensive, and often ends in failure. The Protege platform facilitates the secure, efficient, and privacy-centric exchange of AI training data.
What they're looking for
- PhD or equivalent Master’s Degree + 4+ years industry experience in machine learning, computer science, statistics, engineering, mathematics, economics, or related quantitative fields
- Strong understanding of AI model training pipelines, evaluation methodology, and the role of data in shaping model performance
- Experience working with large, unstructured, or semi-structured datasets used to train or evaluate ML systems
- Experience with reinforcement learning, sequential decision-making, agentic systems, tool-using models, or multi-step model evaluation
- Experience designing tasks, benchmarks, environments, simulations, or evaluation frameworks for real-world model behavior
- Strong intuition for realism, coverage, difficulty, fidelity, and meaningful outcome structure in datasets
More about this role
We are building Protege to solve the biggest unmet need in AI — getting access to the right training data. The process today is time intensive, incredibly expensive, and often ends in failure. The Protege platform facilitates the secure, efficient, and privacy-centric exchange of AI training data.
Solving AI’s data problem is a generational opportunity. We’re backed by world-class investors and already powering partnerships with some of the most ambitious teams in AI. The company that succeeds will be one of the largest in AI — and in tech.
We’re a lean, fast-moving, high-trust team of builders who are obsessed with velocity and impact. Our culture is built for people who thrive on ambiguity, own outcomes, and want to shape the future of data and AI.
DataLab exists because truly useful data is rare — and the frontier of AI development only moves forward when high-quality data makes it possible.
We believe data is one of the most underdeveloped layers of the AI stack. Our work focuses on building and evaluating high-value datasets grounded in real-world workflows and economically meaningful tasks.
We work across multiple domains to create safe, high-fidelity datasets that preserve...
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