below marketmost similar roles pay hereabove market
This role pays more than
99%
of similar roles. Most pay
$183,775–$248,375
— the blue band above.
At the midpoint, this role pays about
$360k
versus about
$216k
for comparable roles.
Based on 240 similar postings.
Employer
About Datadog
Datadog, Inc. is an American company that provides an observability service for cloud-scale applications, providing monitoring of servers, databases, tools, and services, through a SaaS-based data analytics platform.
Datadog currently has
60 open roles
on FindRole.
Listed pay typically runs
$192,000–$240,000
across 59 roles with salary data.
As a Staff Research Scientist within Datadog AI Research, you will serve as a hands-on individual contributor driving research in post-training and autonomous agents. You will own research problems end-to-end, from framing questions to model development and evaluation. Your daily work involves designing and advancing reinforcement learning approaches, post-training methods, and training loops for agents operating in complex environments. You will build simulated environments, synthetic data generation pipelines, and evaluation frameworks to enable scalable training. Key technical requirements include deep expertise in reinforcement learning, AI agents, post-training, and generative modeling. You will translate these advances into scalable capabilities grounded in observability and security while contributing to research publications and open-sourcing model artifacts and benchmarks for the broader research community.
What does a Research Scientist earn?
Median $216250 from 42 postings across 16 companies.
Drive research in agent post-training and reinforcement learning for complex real-world systems.
Own research problems end-to-end from initial framing through experimentation and model development.
Design and advance reinforcement learning approaches and training loops for autonomous agents.
Build simulated environments, synthetic data generation pipelines, and scalable evaluation frameworks.
Set technical standards and review research directions to raise the team's technical bar.
Translate research advances into scalable product capabilities with engineering and product teams.
Contribute to research publications and present findings at top-tier AI conferences.
Open-source key model artifacts and benchmarks to the broader research community.
What we're looking for
You hold a PhD in Computer Science, Machine Learning, or a related field, or have equivalent experience.
You have deep expertise in reinforcement learning, AI agents, post-training, or generative modeling.
You have driven technically ambitious research at meaningful scale as an individual contributor in an industry, startup, or academic setting.
You have extensive hands-on experience designing and implementing reinforcement learning systems, agent 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, or widely used research artifacts.
You have experience setting technical direction through influence and mentoring other researchers or engineers.
You can communicate complex research findings effectively across technical and non-technical audiences.
Machine Learning
Python
Generative AI
Transformers
Self-Supervised Learning
Foundation Models
VLAs
Multimodal Systems
Video Generation
Robotics
AV
ADAS
Generative AI
Machine Learning
Deep Learning
Python
Large Language Models
Retrieval-Augmented Generation
Agentic AI
Data Analytics
AI Model Architectures
Algorithms
Technical Documentation