# Staff Research Scientist - Foundation & World Models **Company**: Datadog **Location**: New York, NY **Experience**: staff **Job type**: full-time **Salary**: $320,000-$400,000 **Category**: Research **Industry**: Technology **Apply**: https://job-boards.greenhouse.io/datadog/jobs/8261937?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_87e61294-bba ## 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. ## Skills ### Required - Computer Science - Machine Learning - Foundation Models - World Models - Multimodal Learning - Generative Modeling - Deep Learning ### Nice to have - Non-text Data --- Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/datadog/jobs/8261937?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)