Senior AI Training Architect — Distributed MoE & RL

NVIDIA; Marseille; On-site; EUR 110,000 - 160,000; Full time

Job summary

NVIDIA is seeking a senior Solutions Architect to support EMEA AI researchers and institutions in training and aligning large-scale models. You will be the technical expert for multi-node GPU deployments, bridging research and engineering across the full training stack.

You will collaborate with product teams, guide customers on training efficiency, RoI and MoE models, and help shape NVIDIA's roadmap based on feedback.

Qualifications

• MS or PhD in Computer Science, Engineering, or equivalent experience.
• 7+ years of practical experience in distributed AI training with multi-node GPU clusters.
• Solid understanding of training infrastructure and how it affects efficiency and scalability.
• Strong proficiency with Megatron-LM, NeMo, or equivalent distributed training frameworks.
• Excellent communication skills with an ability to engage both research scientists and infrastructure engineers.

Responsibilities

• Build strategic technical relationships with leading EMEA AI model builders and collaborators.
• Define the software stack and infrastructure required for large-scale training and post-training workflows (including RL).
• Guide customers through distributed training strategies and post-training recipes using frameworks like PyTorch, Megatron-LM, NeMo.
• Collaborate with NVIDIA product and research teams to present customer needs and feedback.
• Support the developer community through hackathons, demos, and technical conferences.

Skills

Distributed AI training

HPC

Communication skills

Bridge research & engineering

Education

MS or PhD in CS/Engineering

Tools

Megatron-LM

NeMo

PyTorch

Job description

NVIDIA is seeking a senior Solutions Architect to support EMEA AI researchers and institutions in training and aligning large-scale models. You will be the technical expert for multi-node GPU deployments, bridging research and engineering across the full training stack.

You will collaborate with product teams, guide customers on training efficiency, RoI and MoE models, and help shape NVIDIA's roadmap based on feedback.