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Datadog

Research Science Intern (PhD)

Datadog is hiring a Research Science Intern (PhD) in New York and Pittsburgh, United States. It pays $110k-$140k a year and Level rates it ; you can apply on Datadog.

Level's read on this job

  • Builds AI ●●●● is how Level rates this role: the job is building AI systems.
  • Tools and skills the posting cites include Python, PyTorch and GPUs.
  • Level classifies it as an internship.
  • Level lists 396 other open roles at Datadog.

AI in this role

Ph.D. research internship focusing on foundation models, AI agents, and machine learning systems for software observability.

pythonpytorchgpus
ai-agentsai-researchmachine-learningdeep-learningresearchfoundation-models

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.

#LI-Hybrid

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. 

The reasonably estimated yearly salary for this role at Datadog is: $110,000—$140,000 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.

How we rate this

Research Science Intern (PhD) at Datadog rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsAI ResearchMachine learningDeep learningResearchFoundation ModelsPythonPyTorch

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. Tell me about a research question you investigated. What did you find?
  3. Tell me about a project where machine learning was part of your work. What did you do?
  4. Tell me about a project where deep learning was part of your work. What did you do?
  5. Tell me about a project where research was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI agents, AI Research, Machine learning, Deep learning, and Research. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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