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AI Research Scientist - Datadog AI Research (DAIR)

Datadog · Paris

Nouveau
Hybrid Senior 🇬🇧 English
PyTorch DeepSpeed Megatron-LM CUDA Reinforcement learning Generative AI

Description du poste

About the role

Datadog AI Research (DAIR) is looking for a Research Scientist in Paris to partner with Research Engineers on fundamental research problems and work with product and engineering teams to turn research advances into products. The team focuses on two areas: world models for observability (multimodal foundation models covering metrics, traces, logs, topology and events) and trained agents for observability, starting with SRE incident response.

Key responsibilities

  • Conduct research in generative AI and machine learning, building foundation models and trained agents for observability
  • Train multimodal models on large-scale telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure
  • Design and build simulated environments and RL training loops for on-policy agent training and evaluation
  • Work with Product and Engineering teams to integrate multimodal world modeling and autonomous agents into Datadog products
  • Stay up to date on foundation models, world models and RL-based agent research
  • Contribute to research publications, present at top-tier conferences (e.g. NeurIPS, ICLR, ICML) and help open-source model artifacts and benchmarks

Required profile

  • PhD in Computer Science, Machine Learning or a related field, or equivalent experience
  • Deep expertise in generative modeling, world models, AI agents, reinforcement learning or multimodal learning
  • Track record of publications at top-tier venues (NeurIPS, ICLR, ICML, TMLR)
  • Able to explain complex models and research to technical and non-technical audiences

Required skills

  • Extensive experience designing and implementing deep learning models and agents
  • Distributed training frameworks such as DeepSpeed and Megatron-LM
  • Machine learning libraries such as PyTorch
  • Familiarity with efficient training, post-training and inference techniques for large foundation models

Bonus points: bridging research and product applications, writing production data pipelines, and hands-on GPU programming and optimization with CUDA.

What we offer

  • Competitive global benefits
  • New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
  • Close collaboration with colleagues in New York City and Paris
  • Opportunities to attend and present at conferences and meetups
  • Intra-departmental mentor and buddy program
  • Inclusive culture and access to employee resource groups

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Datadog

Paris