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Product Manager II - Model Lab

Datadog - New York, New York, USA

Posted Aug 27, 2025

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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Mental health support
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Learning budget
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Verification
Not verified last checked Jun 13, 2026
Salary
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401(k) match
Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.

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Schedule

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Weekend work
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Application

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About this role

Product Manager II - Model Lab New York, New York, USA As a Product Manager II for Model Lab , you will define and launch Datadog's experiment tracking platform built for teams training and fine-tuning foundational models. Model Lab centralizes metrics, hyperparameters, datasets, code versions, artifacts, and lineage to help ML and AI teams achieve reliable, reproducible, and explainable training runs at scale. This is a 0→1 opportunity to build a new product that will be deeply integrated into Datadog's observability platform. You will shape the product vision, validate the market, and drive execution for a new category-defining offering that serves AI research, ML platform, and applied AI teams. At Datadog, we value our office culture - the relationships it builds, the creativity it fosters, and the collaboration that comes from working together. We operate as a hybrid workplace to help employees create a work-life harmony that fits their needs. What You'll Do: Define the vision and strategy for Model Lab, establishing Datadog's position in experiment tracking and model training observability Lead 0→1 product discovery with AI research teams, ML platform engineers, and infrastructure leaders to deeply understand experiment tracking workflows and pain points Design a system that unifies training metrics, hyperparameters, artifacts, dataset lineage, and model evaluation into a coherent and scalable experience Identify differentiation opportunities vs. competitive alternatives and homegrown internal tooling Partner closely with engineering and design to ship foundational capabilities such as experiment lineage, artifact versioning, distributed training visibility, and reproducibility workflows Collaborate with go-to-market teams

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