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., Bits AI, Watchdog, and Toto), 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 tooling
Implement models, run experiments at scale, and profile for reliability, performance, and cost
Orchestrate distributed training and distributed RL with Ray, including scheduling, scaling, and failure recovery
Make the research stack observable, reproducible, and easier to use
Establish rigorous automated benchmarks and regression tests for forecasting, anomaly detection, multi-modal analysis, agents, and code repair tasks
Collaborate with Research Scientists, Product, and Engineering to integrate advanced AI capabilities into Datadog’s product ecosystem and to harden prototypes into reliable services
Contribute high-quality code, documentation, and open-source artifacts that enable the community and internal teams to reproduce, extend, and evaluate results

Who You Are: You have strong software engineering skills with experience in domains such as observability, SRE, or security
You have depth in distributed computing and ML systems for training and inference at scale; experience with Ray, Slurm, or similar frameworks is a plus
You are proficient in Python, familiar with a systems language (e.g., Rust, C++, or Go), and you are comfortable with modern cloud and data infrastructure
You have practical experience implementing and operating ML training and inference systems (e.g., Py Torch or JAX), including containerization, orchestration, and GPU acceleration
You are familiar with efficient training, fine-tuning, and inference techniques for large foundation models
You can explain design and performance trade-offs clearly to both technical and non-technical audiences
You have a strong interest in open-science and open-source contributions, including establishing rigorous benchmarks and sharing artifacts with the community

Bonus 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 deployments
You are passionate about pushing the boundaries of AI while maintaining a strong focus on customer impact, scalability, and responsible deployment of new technologies
You have hands-on experience with GPU programming and optimization, including experience in CUDA
You have experience writing production data pipelines and applications
You have experience supporting or contributing to research publications

*Datadog 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 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)

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

About Datadog:

Datadog (NASDAQ:

DDOG) 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. Learn more about #DatadogLife on [Instagram](https: //www.instagram.com/datadoghq/?hl=en), LinkedIn, and Datadog Learning Center.Equal Opportunity at Datadog:Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference.

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