Greenhouse ·
full-timeStaff Research Scientist - Foundation & World Models
Datadog · New York, New York, USA; Pittsburgh, Pennsylvania, USA
Datadog is a global SaaS company specializing in cloud-scale monitoring, infrastructure observability, and security for modern technology stacks. As a Staff Research Scientist within the Datadog AI Research team, you will focus on advancing foundation and world models specifically tailored to complex distributed systems. The role involves end-to-end research, from framing technical problems to training large-scale multimodal models on diverse telemetry data such as logs, metrics, traces, and topology. You will operate as a hands-on individual contributor, setting the technical direction for research programs while collaborating with product and engineering teams to integrate these advancements into scalable platform capabilities. This position is well-suited for a researcher with a PhD or equivalent experience who possesses deep expertise in generative modeling, representation learning, and large-scale deep learning. The ideal candidate has a proven track record of influential research, such as publications in top-tier conferences like NeurIPS or ICML, and is comfortable mentoring peers while maintaining a strong focus on experimental rigor and technical execution in a research-heavy environment.
As a Staff Research Scientist within Datadog AI Research (DAIR), you will drive research in foundation models and world models as a hands-on individual contributor. You will advance large-scale pre-training and multimodal learning across the diverse signals generated by distributed systems, including metrics, traces, logs, topology, and events. You will set the technical direction for ambitious research programs, raise the technical bar for the researchers and research engineers around you, and collaborate with Datadog's product and engineering teams to translate research advances into products. What You'll Do: Drive research in foundation models, world models, and multimodal learning, shaping the technical direction of ambitious research programs grounded in observability Own research problems end to end, from framing the question through experimentation, model development, and evaluation Train large-scale multimodal models on diverse telemetry data, including metrics, logs, traces, topology, events, and other non-text modalities Advance approaches to pre-training, representation learning, world modeling, scaling, and evaluation for models that learn the dynamics of complex distributed systems Raise the technical bar across the team by reviewing research directions, mentoring researchers and research engineers, and setting standards for experimental rigor Collaborate with cross-functional teams across Research, Product, and Engineering to translate research advances 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 foundation models, world models, multimodal learning, or generative modeling You have driven technically ambitious research at meaningful scale as an individual contributor, whether in an industry research lab, startup, academic environment, or another research setting You have extensive hands-on experience designing, training, and evaluating large-scale deep learning models (such as large language models), with experience in multimodal or non-text data considered a strong plus 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 set technical direction through influence rather than authority, and you have mentored other researchers or engineers and elevated the quality of work around you You want to stay deeply hands-on in research for the long term, and you can communicate complex research findings effectively across technical and non-technical audiences Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog. About Datadog: 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. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center. Equal Opportunity at Datadog: Datadog is an Affirmative Action and Equal Opportunity Employer and 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 more. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference. Your Privacy: Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. 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 reasonabl
| Role | Staff Research Scientist - Foundation & World Models |
|---|---|
| Company | Datadog |
| Location | New York, New York, USA; Pittsburgh, Pennsylvania, USA |
| Type | full-time |
| Compensation | Not disclosed |
| Posted | 2026-10-07 |
| Deadline | Rolling |
Typical process for this type of role
A general guide — the exact steps for this specific listing may vary; check the original posting for details.
- 1ApplicationSubmit your resume through the apply link.
- 2ScreeningRecruiter reviews your background against the role.
- 3AssessmentA technical test, assignment, or coding round, depending on the role.
- 4Interview(s)One or more rounds with the hiring team.
- 5OfferOffer letter with compensation and start date.
Before you apply
0/4About Datadog
Datadog provides a modern monitoring and security platform designed for developers, IT operations teams, and business users operating in the cloud. The company's platform offers a wide range of capabilities, including infrastructure, network, container, and serverless monitoring, as well as application performance monitoring, log management, and cloud security. These tools are utilized by organizations across various industries, such as financial services, healthcare, retail, and technology, to enable digital transformation and drive collaboration across teams. Datadog employs over 8,100 people globally and continues to expand its presence to support customers across diverse markets and regions.
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