Product Manager II - Model Lab

Datadog Datadog · Enterprise · New York, NY · Product Management

Product Manager II for Model Lab, a new experiment tracking platform for teams training and fine-tuning foundational models. The role involves defining product vision, market validation, and driving execution for a new offering integrated into Datadog's observability platform, serving AI research, ML platform, and applied AI teams.

What you'd actually do

  1. Define the vision and strategy for Model Lab, establishing Datadog’s position in experiment tracking and model training observability
  2. Lead 0→1 product discovery with AI research teams, ML platform engineers, and infrastructure leaders to deeply understand experiment tracking workflows and pain points
  3. Design a system that unifies training metrics, hyperparameters, artifacts, dataset lineage, and model evaluation into a coherent and scalable experience
  4. Identify differentiation opportunities vs. competitive alternatives and homegrown internal tooling
  5. Partner closely with engineering and design to ship foundational capabilities such as experiment lineage, artifact versioning, distributed training visibility, and reproducibility workflows

Skills

Required

  • 4+ years of Product Management experience
  • at least one 0→1 product or major feature launch
  • entrepreneurial and comfortable operating with ambiguity
  • defining problems before defining solutions
  • experience with developer tools, ML infrastructure, data platforms, or AI/LLM systems
  • understand (or can quickly ramp on) modern ML training workflows — distributed training, experiment tracking, hyperparameter tuning, artifact storage, evaluation pipelines
  • familiarity with frameworks such as PyTorch, TensorFlow, JAX, or distributed training frameworks
  • opinionated about product quality and developer experience, especially around APIs, SDKs, and workflows
  • translate highly technical concepts into compelling product narratives
  • comfortable making prioritization tradeoffs in fast-paced, competitive markets
  • thrive in cross-functional environments and can align engineering, design, and GTM around a clear strategy
  • excited to build in a rapidly evolving AI ecosystem

Nice to have

  • passion for building technical products
  • shape the future of AI infrastructure

What the JD emphasized

  • 0→1 opportunity
  • 0→1 product discovery
  • experiment tracking
  • model training observability
  • training metrics
  • hyperparameters
  • artifacts
  • dataset lineage
  • model evaluation
  • experiment lineage
  • artifact versioning
  • distributed training visibility
  • reproducibility workflows
  • developer tools
  • ML infrastructure
  • data platforms
  • AI/LLM systems
  • modern ML training workflows
  • distributed training
  • experiment tracking
  • hyperparameter tuning
  • artifact storage
  • evaluation pipelines
  • APIs
  • SDKs
  • workflows

Other signals

  • 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
  • Partner closely with engineering and design to ship foundational capabilities such as experiment lineage, artifact versioning, distributed training visibility, and reproducibility workflows
  • Translate ambiguous, research-oriented workflows into clear product primitives and APIs