AI Research Scientist - Datadog AI Research (DAIR) | Datadog Careers

Datadog

Quick summary

Work type
On-site
Location
New York, NY
Salary
$140,000–$400,000 / yr
Posted
14 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $204k
This role $270k
$109k most similar roles pay here $431k

This role pays more than 90% of similar roles. Most pay $162,000–$246,150 — the shaded band above. At the midpoint, this role pays about $270k versus about $204k 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 114 open roles on FindRole.

Listed pay typically runs $187,000–$240,000 across 56 roles with salary data.

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View all roles at Datadog

At a glance

TL;DR · AI Research Scientist - Datadog AI Research (DAIR) | Datadog Careers

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As a Research Scientist at Datadog, you will join the AI Research team to tackle high-risk, high-reward problems in cloud observability and security by conducting research in generative AI and machine learning. Your daily tasks include building specialized foundation models and trained agents for observability, training multimodal models on large-scale telemetry data using distributed infrastructure, designing simulated environments for reinforcement learning, and collaborating with cross-functional teams to integrate these capabilities into Datadog’s products. You will need a PhD in Computer Science or related fields, expertise in generative modeling, world models, and reinforcement learning, extensive experience with deep learning frameworks like PyTorch, and a track record of impactful publications at top-tier venues. Familiarity with efficient training techniques for large foundation models and the ability to communicate complex research findings effectively are essential. Bonus points include experience bridging research and real-world applications, passion for customer impact, production data pipeline expertise, and GPU programming skills.

Skills

Python PyTorch DeepSpeed Megatron-LM CUDA NeurIPS ICLR ICML Distributed Training Reinforcement Learning Multimodal Learning GPU Programming Generative AI Large Foundation Models Rapid Prototyping Efficient Inference Data Pipelines

What you'll do

  • Conduct research in generative AI and machine learning to build specialized foundation models for observability.
  • Train multimodal models on large-scale telemetry data using distributed training infrastructure.
  • Design simulated environments and reinforcement learning loops for autonomous agent training.
  • Integrate advanced research capabilities into Datadog's products with cross-functional teams.
  • Stay updated and contribute to the forefront of AI research through publications and presentations.
  • Develop efficient training techniques for large foundation models and optimize post-training inference.

What we're looking for

  • PhD in Computer Science, Machine Learning, or related field with expertise in generative modeling and reinforcement learning.
  • Extensive experience designing and implementing deep learning models and agents using distributed training frameworks like DeepSpeed and PyTorch.
  • Strong background in efficient training techniques for large foundation models and post-training optimization.
  • Track record of impactful publications at top-tier conferences such as NeurIPS, ICLR, ICML.
  • Ability to explain complex AI research findings to both technical and non-technical audiences effectively.

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