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Machine Learning Researcher, RL & Agentic Systems

Protege - Remote, United States

Posted May 28, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
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Relocation assistance
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Childcare support
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Learning budget
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401(k) match
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Market context

Median wage (BLS OEWS)
$116,543 national median
Projected growth (BLS Employment Projections)
+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work
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Application

Cover letter
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Assessment
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Deadline
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Where they hire

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About this role

Machine Learning Researcher, RL & Agentic Systems Remote, United States Company Overview: 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. About DataLab 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 the structure and context needed to train advanced AI systems. Our research spans data quality, evaluation design, privacy-preserving transformation, workflow reconstruction, and task-grounded AI training data. At DataLab, applied research is tightly connected to real-world deployment. Researchers work directly with large-scale datasets, production

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