AI Systems Research Engineer - Multimodal & RL Infra

Free resume; Paris; Hybrid; EUR 90,000 - 150,000; Full time

Job summary

Datadog AI Research in Paris seeks a Research Engineer to partner with Research Scientists, turning ideas into production-ready systems. You will build data, tooling, and infrastructure to enable rapid iteration, trustworthy evaluation, and smooth prototype-to-production transitions.

You will design and run large-scale experiments, orchestrate distributed training with Ray, and contribute to open-source artifacts and publications.

Qualifications

• Experience with distributed training and RL workflows.
• Proficient in Python; familiarity with a systems language (Rust, C++, or Go).
• Experience with PyTorch or JAX; containerization and cloud tooling.

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 RL 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 Datadog's products and to harden prototypes into reliable services

Skills

Distributed computing

RL Infra

ML systems

Ray

Slurm

Python

Systems languages

Tools

Ray

Slurm

Job description

Datadog AI Research in Paris seeks a Research Engineer to partner with Research Scientists, turning ideas into production-ready systems. You will build data, tooling, and infrastructure to enable rapid iteration, trustworthy evaluation, and smooth prototype-to-production transitions.

You will design and run large-scale experiments, orchestrate distributed training with Ray, and contribute to open-source artifacts and publications.