Description
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.
Your responsibilities include:
- Driving research in foundation models, world models, and multimodal learning, shaping the technical direction of ambitious research programs grounded in observability
- Owning research problems end-to-end, from framing the question through experimentation, model development, and evaluation
- Training large-scale multimodal models on diverse telemetry data, including metrics, logs, traces, topology, events, and other non-text modalities
- Advancing approaches to pre-training, representation learning, world modeling, scaling, and evaluation for models that learn the dynamics of complex distributed systems
- Raising the technical bar across the team by reviewing research directions, mentoring researchers and research engineers, and setting standards for experimental rigor
- Collaborating with cross-functional teams across Research, Product, and Engineering to translate research advances into scalable Datadog capabilities
- Contributing to research publications, presenting at top-tier conferences such as NeurIPS, ICLR, and ICML, and helping open-source key model artifacts and benchmarks
To be successful in this role, you should:
- 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
- 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
- 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
- Have a track record of research impact through influential publications, significant model or system contributions, widely used research artifacts, or equivalent technical achievements
- Set technical direction through influence rather than authority, and have mentored other researchers or engineers and elevated the quality of work around you
- Want to stay deeply hands-on in research for the long term, and can communicate complex research findings effectively across technical and non-technical audiences
We offer a competitive salary and equity package, and may include variable compensation. The reasonably estimated yearly salary for this role at Datadog is: $320,000-$400,000 USD. We also offer 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.