About this role
As a Research Manager within Datadog AI Research (DAIR), you will lead a team working on fundamental research in post-training and autonomous agents while remaining deeply engaged in the technical direction of the work. You will advance reinforcement learning, simulated environments, synthetic data generation, and evaluation methods for agents operating across complex real-world systems. You will provide technical leadership to a team of researchers and research engineers, mentor and develop highly technical talent, shape research direction, and collaborate with Datadog’s product and engineering teams to translate research advances into products. This role is designed for an exceptional researcher or technical leader who wants to maintain a strong hands-on research identity while developing and leading a high-performing team.
At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.
What You'll Do:
• 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
Who You Are:
• You hold a PhD in Computer Science, Machine Learning, or a related field, or have equivalent experience, with deep expertise in areas such as reinforcement learning, AI agents, post-training, or generative modeling
• You have demonstrated the ability to lead technically ambitious research at meaningful scale, whether in an industry research lab, startup, academic environment, or another research setting
• You have extensive hands-on experience designing or implementing reinforcement learning systems, agent training methods, simulated environments, synthetic data pipelines, or evaluation frameworks
• You have a track record of research impact through influential publications, significant model or system contributions, widely used research artifacts, or equivalent technical achievements
• You have operated at a senior technical le