AI Research Scientist - Datadog AI Research (DAIR)

DataDog
Paris
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningEducation: phdSkills: ["Python","PyTorch","TensorFlow","CUDA","DeepSpeed","Megatron-LM","Distributed training"]

A research scientist role focused on cutting-edge Generative AI and Machine Learning to build Foundation Models and AI Agents for observability, site reliability engineering, and code repair. You will train large models, publish findings, and collaborate with Product/Engineering to integrate AI capabilities into Datadog’s product ecosystem, advancing research with real-world impact.

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DataDog
DataDog
1 year ago

AI Research Scientist - Datadog AI Research (DAIR)

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Source: Company careers pageValidated by: Fursa AI
Last checked: 7 hours agoStatus: Live

Job Summary

A research scientist role focused on cutting-edge Generative AI and Machine Learning to build Foundation Models and AI Agents for observability, site reliability engineering, and code repair. You will train large models, publish findings, and collaborate with Product/Engineering to integrate AI capabilities into Datadog’s product ecosystem, advancing research with real-world impact.
Location: Paris
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Conduct cutting-edge research in Generative AI and Machine Learning, aiming to build specialized Foundation Models and AI Agents for observability, site reliability engineering, and code repair
  • •Leverage large-scale distributed training infrastructure to pre-train and post-train state-of-the-art models on diverse, real-world telemetry data
  • •Build simulated environments to facilitate on-policy agentic training and evaluation
  • •Lead and contribute to research publications, present findings at top-tier conferences (e.g., NeurIPS, ICLR, ICML), and help open-source key model artifacts and benchmarks
  • •Collaborate with cross-functional teams (e.g., Product, Engineering) to integrate advanced AI capabilities – like multi-modal analysis or automated incident resolution planning – into Datadog’s product ecosystem

Pay and Benefits

Equity and Bonus:Equity
Perks:RsusEspp

Key Requirements

  • •PhD in Computer Science, Machine Learning or related field (or equivalent experience)
  • •Extensive experience designing and implementing deep learning models and agents
  • •Strong background with distributed training frameworks (e.g., DeepSpeed, Megatron-LM) and ML libraries (PyTorch, TensorFlow)
  • •Proven track record of impactful research with publications at top-tier venues (NeurIPS, ICLR, ICML, TMLR)
  • •Familiarity with efficient training, post-training, fine-tuning, and inference techniques for large foundation models
Experience:AI researchCloud observability
Education:PhD / Doctorate
Skills:PythonPyTorchTensorFlowCUDADeepSpeedMegatron-LMDistributed training
Languages:English
Tech Stack:PythonPyTorchTensorFlowCUDADeepSpeedMegatron-LM

Company Brief

DataDog
Provides a cloud-native monitoring and observability platform that unifies metrics, traces, logs, and security signals to help engineering, operations, and security teams monitor and troubleshoot modern applications and infrastructure.
Industry: Developer Tools
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: New York, United States
Founded: 2010
Glassdoor
Glassdoor: 4.1
WebsiteLinkedIn