Datadog AI Research — Scholars Program with Carnegie Mellon University
Datadog AI Research (DAIR) is partnering with Carnegie Mellon University to support a small number of PhD students working on open research problems grounded by ongoing efforts at Datadog/DAIR.
You will frame a problem, run your own experiments, and write up what you find, with compute and data at a scale most academic labs cannot provide. You will collaborate with colleagues working on the same questions.
The Lab And The Research:
DAIR is an industrial research lab motivated by practical challenges in observability and software operation: detecting and diagnosing failures, understanding complex production environments, and helping engineers operate software more effectively. The lab focuses on creating specialized foundation models, post-training and evaluating AI agents, and building frontier-scale machine learning systems. By combining fundamental research with Datadog's large-scale, real-world data and infrastructure, the lab develops new AI capabilities and translates them into practical systems with meaningful impact.
Internship projects are shaped with your DAIR mentor and your CMU faculty advisor. You do not need prior experience with observability, monitoring, or infrastructure.
What You'll Do:
- Own a research project end to end: framing the question, running the experiments, writing it up
- Work directly with a DAIR mentor engaged in the same problem, and stay connected to your advisor and lab
- Publish, and use the work toward your dissertation
- See research reach production, when it works
Who You Are:
- Currently enrolled in a PhD program at Carnegie Mellon in machine learning, computer science, statistics, or a related field
- Depth in at least one area relevant to the research above
- Comfort running real experiments — training models, working with GPUs, reading and reimplementing recent papers
- Evidence you can do research: conference or workshop papers, preprints, open-source contributions, or a lab project you can discuss in depth
- Research taste. You can explain why a problem matters and what would change if it were solved.
- Honest empiricism. You report the ablation that didn't work.
- Support from your faculty advisor.
Not Required:
- A long publication record. How you think matters more than how much you've published.
- Observability, monitoring, or SRE background.
- A perfect match to the areas above.
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.
This job is available in various departments within our company; to conform to US export control regulations, some of these roles may require candidates to be eligible for any required authorizations from the US government.
If possible, please apply using your personal email address instead of your university email address.
Students can sign up for a free Datadog Pro account to learn more about our platform and products.
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Datadog offers a competitive salary for this role and may include additional compensation elements. 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, paid time off, and benefits related to traveling and relocation, if eligible.
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.
Skills Required
- Currently enrolled in a PhD program at Carnegie Mellon University in machine learning, computer science, statistics, or a related field
- Depth in at least one research area relevant to AI, machine learning, foundation models, AI agents, or software operations
- Experience running experiments, training models, working with GPUs, and reading and reimplementing recent research papers
- Evidence of research ability through conference or workshop papers, preprints, open-source contributions, or a lab project
- Ability to explain why a research problem matters and what would change if it were solved
- Support from a Carnegie Mellon faculty advisor
What the Team is Saying
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Datadog Compensation & Benefits Highlights
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Healthcare Strength — Health coverage is described as comprehensive, with medical, dental, and vision plans plus added mental-health resources and wellness support. Feedback suggests virtual-care options and fitness reimbursements further strengthen this area.
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Parental & Family Support — Paid parental leave and broad family-forming benefits (e.g., fertility, adoption, surrogacy) are consistently highlighted. Feedback suggests extras like childcare help and pet-related benefits reinforce an inclusive family focus.
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Equity Value & Accessibility — Employees have access to equity via new-hire grants and a discounted Employee Stock Purchase Plan. Feedback suggests these ownership programs materially enhance total rewards for many roles.
Datadog Insights
What We Do
Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers' entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another.
Why Work With Us
At Datadog, we learn from and celebrate each other daily - each win is a team win. Datadogs solve tough problems, innovate pragmatically, and grow together. We promote from within, provide mentorship and opportunities for career development, and support our colleagues in the process. Best of all? We truly love what we do.
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Employees engage in a combination of remote and on-site work.
We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them and their team.
