Staff Research Scientist - Post-Training for Agents

About the job

Responsibilities

• Drive research in agent post-training and reinforcement learning, shaping technical direction for research programs.
• Own research problems end-to-end, from problem framing to experimentation, model development, and evaluation.
• Design and advance reinforcement learning approaches, post-training methods, and training loops for agents in complex environments.
• Build simulated environments, synthetic data generation approaches, and evaluation frameworks for scalable agent training.
• Elevate the technical bar of the team through research direction reviews, mentoring, and setting experimental rigor standards.
• Collaborate with Research, Product, and Engineering teams to translate autonomous agent advances into Datadog capabilities.
• Contribute to research publications, present at top-tier conferences, and open-source key model artifacts and benchmarks.

Requirements

• PhD in Computer Science, Machine Learning, or related field, or equivalent experience, with deep expertise in reinforcement learning, AI agents, post-training, or generative modeling.
• Proven experience driving technically ambitious research at scale as an individual contributor.
• Extensive hands-on experience designing and 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/system contributions, or widely used research artifacts.
• Ability to set technical direction through influence and mentor researchers/engineers.
• Desire to remain hands-on in research long-term and effectively communicate complex findings.

Benefits

• Competitive salary and equity package
• Potential for variable compensation
• Healthcare, dental, parental planning, and mental health benefits
• 401(k) plan and match
• Paid time off
• Fitness reimbursements
• Discounted employee stock purchase plan