AI Research Engineer - Datadog AI Research (DAIR)

DataDog
Paris
Workplace: OnsiteFull timeFunction: Research & Scientific (R&D)Skills: ["Python","Rust","C++","Go","Ray","Slurm","PyTorch","JAX","CUDA","GPU","Docker","Kubernetes"]

Join Datadog AI Research (DAIR) to convert cutting-edge research in observability, AI agents, and production ML systems into scalable, production-ready tools. You’ll partner with researchers to build data pipelines, training and evaluation workflows, and distributed training infrastructure using Ray, PyTorch/JAX, and cloud platforms. You’ll iterate rapidly, benchmark rigorously, and help harden prototypes into reliable services that power Datadog products.

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FursaFursa
DataDog
DataDog
1 year ago

AI Research Engineer - Datadog AI Research (DAIR)

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Source: Company careers pageValidated by: Fursa AI
Last checked: 28 minutes agoStatus: Live

Job Summary

Join Datadog AI Research (DAIR) to convert cutting-edge research in observability, AI agents, and production ML systems into scalable, production-ready tools. You’ll partner with researchers to build data pipelines, training and evaluation workflows, and distributed training infrastructure using Ray, PyTorch/JAX, and cloud platforms. You’ll iterate rapidly, benchmark rigorously, and help harden prototypes into reliable services that power Datadog products.
Location: Paris
Workplace: Onsite
Employment Type: Full time
Job Function: Research & Scientific (R&D)

Key Responsibilities

  • •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.

Pay and Benefits

Equity and Bonus:Equity
Perks:RsusEsppEquity

Key Requirements

  • •Strong software engineering skills with experience in observability, SRE, or security.
  • •Depth in distributed computing and ML systems for training and inference at scale; experience with Ray, Slurm, or similar frameworks is a plus.
  • •Proficient in Python, familiar with a systems language (e.g., Rust, C++, or Go), and comfortable with modern cloud and data infrastructure.
  • •Practical experience implementing and operating ML training and inference systems (e.g., PyTorch or JAX), including containerization, orchestration, and GPU acceleration.
  • •Familiar with efficient training, fine-tuning, and inference techniques for large foundation models.
Experience:ObservabilitySRESecurityDistributed computingML systemsFoundation models
Skills:PythonRustC++GoRaySlurmPyTorchJAXCUDAGPUDockerKubernetes
Languages:English
Tech Stack:PythonRustC++GoRaySlurmPyTorchJAXCUDADockerKubernetes

Company Brief

DataDog
Provides a cloud-native monitoring and observability platform that unifies metrics, traces, logs, and security signals to help engineering, operations, and security teams monitor and troubleshoot modern applications and infrastructure.
Industry: Developer Tools
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: New York, United States
Founded: 2010
Glassdoor
Glassdoor: 4.1
WebsiteLinkedIn