Staff Research Scientist - Post-Training for Observability Native Models

Datadog
Paris, France

Who this role is best for

Candidates with post-training and multimodal AI research experience will find this role in observability and security decision models rewarding, especially those seeking a hybrid work arrangement in Paris.

Best fit for

  • Individuals with a PhD and experience in AI agents and decision models who thrive in collaborative, hybrid environments
    — “You hold a PhD in Computer Science, Machine Learning, or a related field”
  • Researchers with a history of end-to-end problem ownership and technical leadership in a hybrid workplace setting
    — “You have operated at a senior technical level and have experience leading”
  • Experts in synthetic data generation and evaluation frameworks who want to influence product capabilities
    — “Collaborate with cross-functional teams across Research, Product, and Engineering to translate research advances into scalable Datadog capabilities”

Things to consider

  • This role requires a strong commitment to hands-on research and long-term technical leadership
    — “You want to stay deeply hands-on in research for the long term”
  • The position demands a high level of communication with both technical and non-technical stakeholders
    — “you can communicate complex research findings effectively across technical and non-technical audiences”

How to stand out

  • Highlight your experience in post-training techniques and model evaluation in your resume and interviews
    — “Drive post-training research for multimodal decision models”
  • Emphasize your ability to design simulated environments and synthetic data pipelines
    — “Build simulated environments, synthetic data generation approaches, and evaluation frameworks”
  • Showcase your track record of impactful research contributions through publications or open-source artifacts
    — “You have a track record of research impact through influential publications”
Pace · SteadyCollaboration · MediumAutonomy · HighDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • drive post-training research
  • translate research into products
Typical background
PhD in Computer Science or related fieldresearch experience

Skills & requirements

Required

Post-training MethodsMultimodal Decision ModelsSimulated EnvironmentsSynthetic Data GenerationEvaluation Frameworks

Preferred

Generative ModelingResearch Impact

Stack & domain

AI AgentsDecision ModelsPost-trainingGenerative ModelingTraining MethodsSimulated EnvironmentsSynthetic Data PipelinesEvaluation FrameworksCollaborationCommunicationProblem-solvingResearchObservabilitySecurity

About the role

Original posting from Datadog

As a Staff Research Scientist within Datadog AI Research (DAIR), you will drive work on fundamental research in post-training and multimodal observability-native decision models as a hands-on individual contributor. You will advance post-training approaches, simulated environments, synthetic data generation, and evaluation methods for agents operating across complex real-world systems. You will help set the technical direction for ambitious research programs, raise the technical bar for the researchers and research engineers around you, and collaborate with Datadog's product and engineering teams to translate research advances into products.

At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.

What You'll Do:

Drive post-training research for multimodal decision models and hybrid decision/generative systems to address ambitious research challenges in observability and security.

Own research problems end to end, from framing the question through experimentation, model development, and evaluation

Design and advance post-training methods and training loops for models operating in complex environments

Build simulated environments, synthetic data generation approaches, and evaluation frameworks that enable scalable model training and rigorous measurement

Collaborate with cross-functional teams across Research, Product, and Engineering to translate research advances into scalable Datadog capabilities

Share research findings with external audiences upon reaching significant project milestones.

Who You Are:

You hold a PhD in Computer Science, Machine Learning, or a related field, or have equivalent experience, with deep expertise in areas such as AI agents, decision models, post-training, or generative modeling

You have driven technically ambitious research at meaningful scale as an individual contributor, whether in an industry research lab, startup, academic environment, or another research setting

You have extensive hands-on experience designing or implementing training methods, simulated environments, synthetic data pipelines, or evaluation frameworks

You have a track record of research impact through influential publications, significant model or system contributions, widely used research artifacts, or equivalent technical achievements

You have operated at a senior technical level and have experience leading, You set technical direction through influence rather than authority, and you have mentored other researchers or engineers and elevated the quality of work around you

You want to stay deeply hands-on in research for the long term, and you can communicate complex research findings effectively across technical and non-technical audiences

Datadog values people from all walks of life. We know 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 experience, we encourage you to apply.

#LI-Hybrid

About Datadog: 

Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack 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.

Source: Datadog careers

Similar roles

More roles at Datadog