PyTorch · Foundation Models
As a Staff Research Scientist within Datadog AI Research ( DAIR ), you will drive fundamental research in foundation models and multimodality 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 help 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.
At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.
What You'll Do
Drive research in foundation models and multimodal learning, shaping the technical direction for ambitious research programs grounded in observability and security
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, scaling, and evaluation for models that learn the dynamics of complex distributed systems
Collaborate with cross-functional teams across Research, Product, and Engineering to translate research advances