AI Research Engineer - Datadog AI Research (DAIR)
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About This Role
Datadog is seeking an AI Research Engineer to partner with Research Scientists, turning research ideas into working systems and building data, tooling, and infrastructure for rapid iteration and trustworthy evaluation. The role focuses on high-risk, high-reward problems in cloud observability and security, specifically World Models for Observability and Trained Agents for Observability. The ideal candidate has depth in distributed computing, RL Infra, and ML systems, with experience in Python, systems languages, and modern cloud and data infrastructure.
Key ResponsibilitiesAI-extracted
- 1Build and operate multimodal data pipelines, training and evaluation infrastructure, benchmarks, and internal tooling
- 2Implement models, run experiments at scale, and profile for reliability, performance, and cost
- 3Build simulation environments and replay infrastructure for agent training and evaluation
- 4Orchestrate distributed training and distributed RL with Ray, including scheduling, scaling, and failure recovery
- 5Collaborate with Research Scientists, Product, and Engineering to integrate capabilities into Datadog's products
- 6Contribute to research publications at top-tier conferences
RequirementsAI-extracted
- Depth in distributed computing, RL Infra, and ML systems for training and inference at scale
- Experience with Ray, Slurm, or similar frameworks is a plus
- Proficiency in Python, familiarity with a systems language, and comfort with modern cloud and data infrastructure
- Practical experience implementing and operating ML training and inference systems
- Ability to explain design and performance trade-offs clearly to both technical and non-technical audiences
Perks & BenefitsAI-extracted
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