AI Research Engineer – Get A Job.ai AI Research (DAIR)

Responsibilities

We are representing a confidential cloud observability organization seeking an AI Research Engineer in Paris. You will partner with Research Scientists to build the infrastructure, tooling, and data pipelines that transform research concepts into production-ready systems.

In this role, you will:

• 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 production systems and harden prototypes into reliable services
• Contribute to research publications at top-tier conferences such as NeurIPS, ICLR, and ICML, and produce high-quality code, documentation, and open-source artifacts

What We're Looking For

Required qualifications:

• Depth in distributed computing, RL infrastructure, and ML systems for training and inference at scale; experience with Ray, Slurm, or similar frameworks is a plus
• Proficiency in Python, familiarity with a systems language such as Rust, C++, or Go, and comfort with modern cloud and data infrastructure
• Practical experience implementing and operating ML training and inference systems using PyTorch or JAX, including containerization, orchestration, and GPU acceleration
• Practical experience with large-scale model training and fine-tuning, including frameworks like Megatron-LM, DeepSpeed, SkyRL, VeRL, or TorchTitan, and techniques such as SFT, RLVR, RLHF, and efficient inference
• Ability to explain design and performance trade-offs clearly to both technical and non-technical audiences
• Experience supporting or contributing to research publications

Bonus qualifications:

• Strong software engineering skills with experience in domains such as observability, SRE, or security
• Experience bridging research prototypes and real-world product applications, especially with large foundation models, world models, or RL-trained agents
• Passion for pushing the boundaries of AI with a focus on customer impact and scalable deployment
• Hands-on experience with GPU programming and optimization, including CUDA
• Experience writing production data pipelines and applications
• Experience building simulation or sandbox environments for agent training

How We Work With You

Candidates apply directly through Get A Job.ai. Our talent team will screen your application and arrange an initial conversation. If there's a strong match, we will submit your profile to our client for consideration. Please do not contact the client directly—all communication flows through Get A Job.ai to ensure a smooth and professional process.

Pay

Compensation details will be discussed during the screening process based on experience and qualifications.

Equal Opportunity: Get A Job.ai is committed to inclusive hiring practices. We welcome applicants from all backgrounds and experiences.