Staff Research Scientist - Foundation & World Models
$320k - $400k • Remote • New York, New York, USA; Pittsburgh, Pennsylvania, USA
Posted 10d ago
Job Location
New York, New York, USA; Pittsburgh, Pennsylvania, USA
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Research Engineer
About the job
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.
Responsibilities
- 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.
Requirements
- PhD in Computer Science, Machine Learning, or a related field, or equivalent experience, with deep expertise in areas such as foundation models, world models, multimodal learning, or generative modeling.
- Proven experience driving technically ambitious research at meaningful scale as an individual contributor.
- Extensive hands-on experience designing, training, and evaluating large-scale deep learning models (such as large language models).
- Experience in multimodal or non-text data considered a strong plus.
- Track record of research impact through influential publications, significant model or system contributions, or widely used research artifacts.
- Ability to set technical direction through influence rather than authority.
- Experience mentoring other researchers or engineers and elevating the quality of work around you.
- Desire to stay deeply hands-on in research for the long term.
- Effective communication of complex research findings across technical and non-technical audiences.
Benefits
- Competitive salary and equity package
- May include 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