Research Manager - Post-Training for Agents (NORAM)

Datadog is hiring a Research Manager within Datadog AI Research to lead fundamental research in post-training and autonomous agents while providing technical direction. The role advances reinforcement learning, simulated environments, synthetic data generation, and evaluation methods, and translates research advances into products in collaboration with product and engineering teams.

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