
AI Research Scientist - Datadog AI Research (DAIR)
Datadog · New York, NY
- On site
- Full-time
- $270,000 / year
- New York, NY
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Subject: Interested in the AI Research Scientist - Datadog AI Research (DAIR) role at Datadog
Hi Avery — I came across the AI Research Scientist - Datadog AI Research (DAIR) opening and wanted to reach out directly. I've spent the last few years doing exactly this kind of work, and Datadog stood out because…
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Job highlights
- Research AI foundation models and agents.
- Train multimodal models on telemetry data.
- Develop simulation environments for RL.
- Integrate AI into Datadog products.
- Publish research and attend conferences.
About the role
AI Research Scientist - Datadog AI Research (DAIR)
As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI, Bits Evolve, and our time series foundation model), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security.
Research Areas:
We are focused on two research areas:
- World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents.
- Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost.
What You'll Do:
- 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
Who You Are:
- 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)
- 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)
- Track record of impactful publications at top-tier venues (e.g., NeurIPS, ICLR, ICML, TMLR)
- Familiar with efficient training, post-training, and inference techniques for large foundation models
- Ability to explain complex models and research findings to both technical and non-technical audiences
Bonus Points:
- Experience bridging research and real-world product applications, especially with large foundation models, world models, or RL-trained agents
- Passion for pushing the boundaries of AI with a focus on customer impact and scalable deployment
- Experience writing production data pipelines and applications
- Hands-on experience with GPU programming and optimization, including CUDA
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 technology 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, LinkedIn, and Datadog Learning Center.
Equal Opportunity at Datadog:
Datadog is an Affirmative Action and Equal Opportunity Employer and 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 more. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference.
Your Privacy:
Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.
Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.
The reasonably estimated yearly salary for this role at Datadog is: $140,000—$400,000 USD
About Datadog:
Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stacks to manage complexity at scale. It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers. Trusted globally by Fortune 500 companies and high-growth AI leaders, Datadog enables businesses to move faster with clarity and confidence. Learn more about #DatadogLife on Instagram, 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.
Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications.
Privacy and AI Guidelines:
Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.
Key skills/competency
- AI Research Scientist
- Generative AI
- Machine Learning
- Foundation Models
- World Models
- AI Agents
- Reinforcement Learning
- Multimodal Learning
- Deep Learning
- Distributed Training
Skills & topics
- AI Research Scientist
- Generative AI
- Machine Learning
- Foundation Models
- World Models
- AI Agents
- Reinforcement Learning
- Multimodal Learning
- Deep Learning
- Distributed Training
- Observability
- Cloud Security
- PyTorch
- DeepSpeed
- Megatron-LM
- NeurIPS
- ICLR
- ICML
- Research Scientist
- AI Engineer
How to get hired
- Tailor your resume: Highlight your PhD, research publications, and experience with generative AI, world models, and RL.
- Showcase relevant experience: Emphasize your background in deep learning, distributed training frameworks (DeepSpeed, Megatron-LM), and PyTorch.
- Demonstrate impact: Clearly articulate your contributions to impactful publications at top-tier conferences like NeurIPS or ICLR.
- Prepare for technical interviews: Be ready to discuss complex models and research findings, and potentially demonstrate coding skills in Python/PyTorch.
- Highlight product-mindset: If you have experience bridging research with product applications, make sure to mention it.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the main research areas for an AI Research Scientist at Datadog?
- The AI Research Scientist role at Datadog focuses on two primary areas: 'World Models for Observability,' which involves training multimodal foundation models for distributed systems, and 'Trained Agents for Observability,' focusing on post-training models to operate autonomously for tasks like SRE incident response and code repair.
- What qualifications are essential for the AI Research Scientist position at Datadog?
- Essential qualifications include a PhD in Computer Science, Machine Learning, or a related field, with deep expertise in generative modeling, world models, AI agents, reinforcement learning, or multimodal learning. Extensive experience in designing and implementing deep learning models and agents, with strong background in distributed training frameworks and ML libraries like PyTorch, is also required. A track record of impactful publications at top-tier venues is crucial.
- What kind of projects will an AI Research Scientist work on at Datadog?
- You will conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability. This includes training multimodal models on large-scale telemetry data, designing simulation environments and RL training loops, and integrating these capabilities into Datadog's products.
- Does Datadog encourage research publication for its AI Research Scientists?
- Yes, Datadog strongly encourages its AI Research Scientists to contribute to research publications and present findings at top-tier conferences such as NeurIPS, ICLR, and ICML. They also support open-sourcing key model artifacts and benchmarks.
- What is the expected salary range for an AI Research Scientist at Datadog?
- The reasonably estimated yearly salary for this role at Datadog ranges from $140,000 to $400,000 USD, with actual compensation depending on factors like skills, qualifications, and experience.
- What are the benefits of working as an AI Research Scientist at Datadog?
- Datadog offers competitive global benefits, including new hire stock equity, employee stock purchase plans, opportunities for professional development, conference attendance, and an inclusive company culture with employee resource groups. You'll also collaborate with talented colleagues in New York City and Paris.
- What programming languages and frameworks are commonly used for this AI Research Scientist role?
