# AI Research Engineer - Datadog AI Research

**Company:** [Datadog](https://hotfix.jobs/companies/datadog)
**Location:** Paris, France
**Role:** AI Research
**Skills:** Python, Ray, Slurm, Rust, C++, Go, PyTorch, JAX, Megatron-Lm, Deepspeed, CUDA, Kubernetes, RLHF, Quantization, Speculative Decoding
**Posted:** 2026-08-12

> Builds data pipelines, distributed training infrastructure, simulation environments, and evaluation systems for multimodal world models and reinforcement-learning agents. The role partners with research scientists to scale experiments and turn prototypes into reliable observability and security products.

## Job Description

## Responsibilities
- Build and operate multimodal data pipelines, training and evaluation infrastructure, benchmarks, and internal tooling.
- Implement models, run experiments at scale, and profile for reliability, performance, and cost.
- Build simulation environments and replay infrastructure for agent training and evaluation.
- Orchestrate distributed training and distributed reinforcement learning with Ray, including scheduling, scaling, and failure recovery.
- Establish rigorous automated benchmarks and regression tests for world model predictions, agent performance, and simulation fidelity.
- Collaborate with Research Scientists, Product, and Engineering to integrate capabilities into products and harden prototypes into reliable services.
- Contribute to research publications at top-tier conferences such as NeurIPS, ICLR, and ICML.
- Produce high-quality code, documentation, and open-source artifacts.

## Requirements
- Depth in distributed computing, reinforcement-learning infrastructure, and machine-learning systems for training and inference at scale.
- Experience with Ray, Slurm, or similar frameworks is a plus.
- Proficiency in Python and familiarity with a systems language such as Rust, C++, or Go.
- Comfort with modern cloud and data infrastructure.
- Practical experience implementing and operating ML training and inference systems such as PyTorch or JAX.
- Experience with containerization, orchestration, and GPU acceleration.
- Experience with large-scale model training and fine-tuning, including frameworks such as Megatron-LM, DeepSpeed, SkyRL, VeRL, or TorchTitan.
- Familiarity with SFT, RLVR, RLHF, quantization, and speculative decoding.
- Ability to explain design and performance trade-offs clearly to technical and non-technical audiences.
- Experience supporting or contributing to research publications.

## Nice-to-haves
- Strong software engineering skills in observability, SRE, or security.
- Experience bridging research prototypes and real-world product applications, especially with large foundation models, world models, or RL-trained agents.
- Hands-on GPU programming and optimization, including CUDA.
- Experience writing production data pipelines and applications.
- Experience building simulation or sandbox environments for agent training.

## Benefits
- Competitive global benefits.
- New-hire stock equity (RSUs) and employee stock purchase plan (ESPP).
- Collaboration with colleagues across Datadog offices in New York City and Paris.
- Opportunities to attend and present at conferences and meetups.
- Intra-departmental mentor and buddy program.
- Inclusive company culture and access to Community Guilds.

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