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Protege · 2 weeks ago

Product Manager, Data Lab

United States

Full-time

Remote

Senior Level

5+ years exp

Protege is building a platform to solve the biggest unmet need in AI by facilitating the secure and efficient exchange of training data. The Product Manager, Data Lab will translate cutting-edge AI research into scalable product capabilities, working closely with research scientists and ML engineers to enhance experimentation and product features.

AnalyticsArtificial Intelligence (AI)Data Management

Responsibilities

Partner closely with Data Lab scientists to understand how models are being trained, evaluated, and iterated today

Translate experimental workflows (data curation, labeling, evaluation, fine-tuning, feedback loops) into scalable product and platform capabilities

Identify patterns across experiments that are worth standardizing versus those that should remain bespoke

Lead product discovery and execution for internal tools that support modern AI development:

Dataset versioning

Evaluation pipelines

Annotation and human-in-the-loop workflows

Experiment tracking and reproducibility

Ensure tooling reflects real-world frontier practices, not academic abstractions

Serve as the primary product interface for the Data Lab

Translate research intuition into product requirements engineers can build against

Help researchers reason about tradeoffs between novelty, robustness, and scalability

Collaborate with Platform and Vertical PMs to ensure new capabilities integrate cleanly into customer-facing products

Decide when an experimental capability is ready to move from 'research mode' to 'product mode'

Apply an 80/20 mindset without undermining scientific rigor

Sunset or deprioritize tools and ideas that do not meaningfully advance AI development velocity or data quality

Define success metrics tied to:

Experiment cycle time

Researcher productivity

Adoption of internal tools

Downstream impact on customer data products

Use qualitative and quantitative feedback to continuously iterate

Qualification

Product ManagementAI/ML PlatformsData InfrastructureExperiment TrackingDataset VersioningHuman-in-the-loop WorkflowsEvaluation PipelinesInfluencing Without AuthorityIterative LearningTechnical Stakeholder EngagementCollaborationCommunication

Required

5+ years of product management experience, ideally in AI/ML platforms, developer tools, data infrastructure, or internal research tooling

Strong experience working with highly technical stakeholders

Proven ability to lead ambiguous, zero-to-one initiatives

Hands-on or adjacent experience with how frontier AI models are built today — including large-scale training, fine-tuning, evaluation, and data iteration

Understanding of concepts like training data quality vs quantity tradeoffs, evaluation benchmarks vs real-world performance, human feedback loops, multimodal data challenges

Ability to have credible conversations with PhD-level researchers and senior ML engineers

Ability to turn complex technical systems into clear product decisions

Excellent communicator across research, engineering, and product

Comfortable influencing without authority

Bias toward shipping, learning, and iterating