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Datadog

Builds monitoring and security tools for clouds

AI Research Scientist

AI ResearchUpdated on Nov 13
Full-time$320k - $400k /yrIn-person

About the Job

Requirements

  • A PhD in Computer Science, Machine Learning, or a related field, or equivalent experience.
  • Deep expertise in generative modeling, AI agents, decision models, or reinforcement learning.
  • Extensive experience designing and implementing deep learning models and agents.
  • A strong background in distributed training frameworks such as DeepSpeed and Megatron-LM, and machine learning libraries such as PyTorch and TensorFlow.
  • A proven track record of impactful research with publications at top-tier venues such as NeurIPS, ICLR, ICML, or TMLR.
  • Familiarity with efficient training, post-training, fine-tuning, and inference techniques for large foundation models.
  • Ability to explain complex models and research findings to technical and non-technical audiences.
  • Strong interest in open science and open-source contributions, including establishing rigorous benchmarks and sharing research with the community.

Responsibilities

  • Conduct research in generative AI and machine learning to build specialized foundation models and AI agents for observability, site reliability engineering, and code repair.
  • Use large-scale distributed training infrastructure to pre-train and post-train models on diverse, real-world telemetry data.
  • Build simulated environments for on-policy agentic training and evaluation.
  • Share research findings with external audiences upon reaching significant project milestones.
  • Collaborate with Product and Engineering teams to integrate capabilities such as multimodal analysis and automated incident resolution planning into Datadog products.
  • Engage with the external research community and stay current with large language model, foundation model, and generative AI research.
  • Participate in reading groups and mentor interns to foster scientific rigor and practical impact.

Desired Qualifications

  • Ability to bridge cutting-edge research and real-world product applications, particularly involving large foundation models, generative AI agents, or domain-specific large language model deployments.
  • Experience writing production data pipelines and applications.
  • Hands-on experience with GPU programming and optimization, including CUDA.

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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