Research Manager - Post-Training for Agents

Datadog
New York, NY
Hybrid

Who this role is best for

A natural match if you have hands-on research experience in reinforcement learning and agent training, and are comfortable with hybrid work arrangements in New York.

Best fit for

  • Candidates with a PhD and hands-on experience in reinforcement learning and agent systems
    — “You hold a PhD in Computer Science, Machine Learning, or a related field, or have equivalent experience”
  • Individuals who have led large-scale research initiatives in AI and observability domains
    — “You have demonstrated the ability to lead technically ambitious research at meaningful scale”
  • People who want to maintain a strong technical identity while leading a team
    — “you want to develop and support a research team while maintaining a strong technical identity”

Things to consider

  • Hybrid work arrangement may require in-office presence in New York City
    — “We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony”
  • The role demands a balance between high-level strategy and hands-on technical execution
    — “You will lead a team working on fundamental research... while remaining deeply engaged in the technical direction of the work”

How to stand out

  • Emphasize your experience in translating research into production systems
    — “collaborate with Datadog’s product and engineering teams to translate research advances into products”
  • Highlight contributions to influential publications or open-source projects
    — “Contribute to research publications, present at top-tier conferences... and help open-source key model artifacts”
  • Showcase your ability to mentor and lead technical teams effectively
    — “You have experience leading, mentoring, and developing teams of researchers or engineers”
  • Demonstrate hands-on capabilities in building simulated environments and evaluation frameworks
    — “Build simulated environments, synthetic data generation approaches, and evaluation frameworks”
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • publishing research papers
  • presenting at top-tier conferences
  • open-sourcing key model artifacts
Typical background
PhD in Computer Science, Machine Learning, or related fieldexperience leading research teams

Skills & requirements

Required

Reinforcement LearningPost-training MethodsAgent TrainingSimulated EnvironmentsSynthetic Data GenerationEvaluation FrameworksTechnical LeadershipMentoring

Preferred

Generative ModelingAgentic Coding

Stack & domain

Reinforcement LearningSimulated EnvironmentsSynthetic Data GenerationEvaluation MethodsLeadershipMentoringCollaborationAIMachine LearningObservabilitySecurity

About the role

Original posting from Datadog

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 level and have experience leading, mentoring, and developing teams of researchers or engineers, while remaining deeply hands-on in technical direction and execution 

You want to develop and support a research team while maintaining a strong technical identity, and you can communicate complex research findings effectively across technical and non-technical audiences 

Datadog values people from all walks of life. We know not everyone will meet all the above qualifications on day one. That’s okay. If you’re passionate about technology and want to grow your experience, we encourage you to apply. 

Benefits and Growth: 

Competitive global benefits 

New hire stock equity (RSUs) and employee stock purchase plan (ESPP)

Opportunity to collaborate closely with colleagues across the Datadog offices in New York City and Paris 

Opportunity to attend and present at conferences and meetups 

Intra-departmental mentor and buddy program for in-house networking

An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups) 

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

#LI-Hybrid

Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.

The reasonably estimated yearly salary for this role at Datadog is:$244,000—$305,000 USD

About Datadog: 

Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack to manage complexity at scale. It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers. Trusted globally by Fortune 500 companies and high-growth AI leaders, Datadog enables businesses to move faster with clarity and confidence. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center.

Equal Opportunity at Datadog:

Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference. 

Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications. 

Privacy and AI Guidelines:

Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.

Source: Datadog careers

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