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Datadog

Builds monitoring and security tools for clouds

Staff Research Scientist - Foundation & World Models

AI ResearchUpdated on Nov 13
Full-time

About the Job

Requirements

  • You hold a PhD in Computer Science, Machine Learning, or a related field, or have equivalent experience, with deep expertise in areas such as foundation models, world models, multimodal learning, or generative modeling.
  • You have driven technically ambitious research at meaningful scale as an individual contributor, whether in an industry research lab, startup, academic environment, or another research setting.
  • You have extensive hands-on experience designing, training, or evaluating large-scale deep learning models, such as large language models; experience in multimodal or non-text data is a strong plus.
  • You have a track record of research impact through influential publications, significant model or system contributions, widely used research artifacts, or equivalent technical achievements.
  • You set technical direction through influence rather than authority, and you have mentored other researchers or engineers and elevated the quality of work around you.
  • You want to stay deeply hands-on in research for the long term, and you can communicate complex research findings effectively across technical and non-technical audiences.

Responsibilities

  • Drive research in foundation models and multimodal learning, shaping the technical direction for ambitious research programs grounded in observability and security.
  • Own research problems end to end, from framing the question through experimentation, model development, and evaluation.
  • Train large-scale multimodal models on diverse telemetry data, including metrics, logs, traces, topology, events, and other non-text modalities.
  • Advance approaches to pre-training, representation learning, scaling, and evaluation for models that learn the dynamics of complex distributed systems.
  • Collaborate with cross-functional teams across Research, Product, and Engineering to translate research advances into scalable Datadog capabilities.
  • Share research findings with external audiences upon reaching significant project milestones.

About the Company

Datadog

Builds monitoring and security tools for clouds

Datadog builds monitoring and security software for developers and operations teams that run cloud applications, giving them a shared view of system health and performance. Its platform links infrastructure monitoring with application performance and log analysis so teams trace a problem across the systems involved. Software agents and integrations collect operational data, which teams explore through dashboards and alerts to find failures, investigate threats and improve the customer experience. The company sells subscriptions to individual products and combined plans, with charges tied to the resources and data monitored. Datadog was founded in 2010 and is headquartered in New York City.

Company size
5,001-10,000
Company stage
IPO
Headquarters
New York City, New York
Founded
2010

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