Datadog
Staff Research Scientist - Foundation & World Models
$320K–$400K
New York, New York, USA +2 · Staff · Full-time · Posted Oct 7, 2026
- Location
- New York, New York, USA
Pittsburgh, Pennsylvania, USA
New York, NY, United States - Experience
- No specific number of years stated; asks for research at meaningful scale and extensive hands-on large-scale deep learning experience.
- Education
- PhD in Computer Science, Machine Learning, or a related field, or equivalent experience.
About the job
Leads hands-on research and development of foundation and world models trained on multimodal observability data, translating research advances into Datadog products.
What you'll do
- Drive research programs in foundation models, world models, multimodal learning, pre-training, and evaluation.
- Own research end to end, including problem framing, experimentation, model development, and evaluation; train large-scale models on telemetry data.
- Set research standards, mentor colleagues, collaborate with Product and Engineering, and contribute to publications and open-source artifacts.
What they ask for
- Deep expertise in foundation models, world models, multimodal learning, or generative modeling.
- Hands-on experience designing, training, and evaluating large-scale deep learning models.
- Track record of research impact through publications, model or system contributions, research artifacts, or equivalent achievements.
- Experience setting technical direction, mentoring researchers or engineers, and communicating research findings.
Nice to have
- Experience with multimodal or non-text data.
Pay
$320,000–$400,000 USD yearly salary (base salary)
Tools
metrics, traces, logs, topology, events, NeurIPS, ICLR, ICML
AI focus
Research and train foundation and world models to learn from multimodal observability telemetry and the dynamics of complex distributed systems.
Model-written summary · the original posting is authoritative