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Research Manager - Post-Training for Agents

Datadog· Research
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Hybrid (New York, NY), Hybrid (Paris)$244k - $305kfull-timePosted 1w ago

About the role

Lead a team in Datadog AI Research (DAIR) focusing on post-training and autonomous agents, guiding research direction and translating advances into scalable Datadog capabilities. Hybrid workplace with offices in New York City and Paris.

Responsibilities

  • Lead research in agent post-training and reinforcement learning, setting the technical direction for ambitious research programs grounded in observability and security
  • Guide and mentor researchers and research engineers while remaining closely involved in research strategy, experimentation, model development, and technical problem-solving
  • Design and advance reinforcement learning approaches, post-training methods, and training loops for agents operating in complex environments
  • Build simulated environments, synthetic data generation approaches, and evaluation frameworks that enable scalable agent training and rigorous measurement
  • Collaborate with cross-functional teams across Research, Product, and Engineering to translate advances in autonomous agents into scalable Datadog capabilities
  • Contribute to research publications, present at top-tier conferences such as NeurIPS, ICLR, and ICML, and help open-source key model artifacts and benchmarks

Qualifications

  • PhD in Computer Science, Machine Learning, or a related field, or equivalent experience, with deep expertise in reinforcement learning, AI agents, post-training, or generative modeling
  • experience leading technically ambitious research at meaningful scale
  • hands-on experience designing or implementing reinforcement learning systems, agent training methods, simulated environments, synthetic data pipelines, or evaluation frameworks
  • track record of research impact through influential publications, significant model or system contributions, widely used research artifacts, or equivalent technical achievements
  • experience leading, mentoring, and developing teams of researchers or engineers while remaining hands-on in technical direction and execution
  • ability to communicate complex research findings effectively across technical and non-technical audiences

Skills

Required:Reinforcement learningPost-training methodsSimulated environmentsSynthetic data pipelinesMentoring and leadership

Benefits

  • Competitive global benefits
  • New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
  • Opportunity to collaborate with colleagues in New York City and Paris
  • Attend and present at conferences and meetups
  • Intra-departmental mentor and buddy program
  • Inclusive culture with Community Guilds
Last updated Oct 22, 2026. Interested? Apply on the company site.

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