AI Research Scientist

Datadog is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another.

• Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability.
• Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure.
• Design and build simulated environments and RL training loops for on-policy agent training and evaluation.
• Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products.
• Stay at the forefront of foundation models, world models, and RL-based agent research.
• Contribute to research publications, present at top-tier conferences (e.g., NeurIPS, ICLR, ICML), and help open-source key model artifacts and benchmarks.

• You hold a PhD in Computer Science, Machine Learning, or a related field, with deep expertise in areas like generative modeling, world models, AI agents, reinforcement learning, or multimodal learning (or have equivalent experience).
• You have extensive experience designing and implementing deep learning models and agents, with a strong background in distributed training frameworks (e.g., DeepSpeed, Megatron-LM) and ML libraries (PyTorch).
• You have a track record of impactful publications at top-tier venues (e.g., NeurIPS, ICLR, ICML, TMLR).
• You are familiar with efficient training, post-training, and inference techniques for large foundation models.
• You can explain complex models and research findings to both technical and non-technical audiences.

• Competitive global benefits.
• New hire stock equity (RSUs) and employee stock purchase plan (ESPP).
• Opportunity to collaborate closely with colleagues across the Datadog offices in New York City and Paris.
• Opportunity to attend and present at conferences and meetups.
• Intra-departmental mentor and buddy program for in-house networking.
• An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups).