As a research engineer on our team, you will partner with research scientists to turn research ideas into working systems; building the data, tooling, and infrastructure that enable rapid iteration, trustworthy evaluation, and a smooth path from prototype to production.Building on our proven track record of AI-powered solutions (e.g., , , and ), Datadog AI Research is tackling high-risk, high-reward projects grounded in real-world challenges in cloud observability and security.We are currently focused on three key research areas:Observability Foundation Models - Building state-of-the-art models for advanced forecasting, anomaly detection, and multi-modal telemetry analysis (logs, metrics, traces, etc.). These models will also provide the foundation for our agents (described below) to natively analyze telemetry data.Site Reliability Engineering (SRE) Autonomous Agents - Creating AI agents to automatically detect, diagnose, and resolve incidents in production environments, pushing the boundaries of multi-step planning, reasoning, and domain-specific knowledge.Production Code Repair Agents - Developing agents and models that leverage code, logs, runtime data, and other signals to identify, fix, and even preempt performance issues and security vulnerabilities in production code.What You'll Do:Build and operate datasets, training and evaluation pipelines, benchmarks, and internal toolingImplement models, run experiments at scale, and profile for reliability, performance, and costOrchestrate distributed training and distributed RL with Ray, including scheduling, scaling, and failure recoveryMake the research stack observable, reproducible, and easier to useEstablish rigorous automated benchmarks and regression tests for forecasting, anomaly detection, multi-modal analysis, agents, and code repair tasksCollaborate with Research Scientists, Product, and Engineering to integrate advanced AI capabilities into Datadog's product ecosystem and to harden prototypes into reliable servicesContribute high-quality code, documentation, and open-source artifacts that enable the community and internal teams to reproduce, extend, and evaluate resultsWho You Are:You have strong software engineering skills with experience in domains such as observability, SRE, or securityYou have depth in distributed computing and ML systems for training and inference at scale; experience with Ray, Slurm, or similar frameworks is a plusYou are proficient in Python, familiar with a systems language (e.g., Rust, C++, or Go), and you are comfortable with modern cloud and data infrastructureYou have practical experience implementing and operating ML training and inference systems (e.g., PyTorch or JAX), including containerization, orchestration, and GPU accelerationYou are familiar with efficient training, fine-tuning, and inference techniques for large foundation modelsYou can explain design and performance trade-offs clearly to both technical and non-technical audiencesYou have a strong interest in open-science and open-source contributions, including establishing rigorous benchmarks and sharing artifacts with the communityBonus Points:You have a demonstrated ability to bridge cutting-edge research prototypes and real-world product applications, ideally with large foundation models, generative AI agents, or domain-specific LLM deploymentsYou are passionate about pushing the boundaries of AI while maintaining a strong focus on customer impact, scalability, and responsible deployment of new technologiesYou have hands-on experience with GPU programming and optimization, including experience in CUDAYou have experience writing production data pipelines and applicationsYou have experience supporting or contributing to research publicationsDatadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you're passionate about AI Research and want to grow your skills, we encourage you to apply.Benefits and Growth:Competitive global benefitsNew 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 ParisOpportunity to attend and present at conferences and meetupsIntra-departmental mentor and buddy program for in-house networkingAn inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.
