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Tech Engagement Lead, AI Labs - EMEA

NVIDIA· Account Mgr, Dev Relations
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Hybrid (France), Hybrid (UK), Remotefull-timePosted 1mo ago

About the role

Technical Engagement Lead to collaborate with frontier AI labs and model builders, driving integration of NVIDIA’s platform (GPUs, systems, software libraries) into research, training, post-training, inference, and emerging AI workloads; influence product roadmap and collaborate across NVIDIA teams and external partners.

Responsibilities

  • Lead technical engagements: Build trusted relationships with senior research, engineering, and infrastructure leaders at frontier AI labs and model builders. Serve as a primary technical point of contact across NVIDIA and the partner organization.
  • Understand the latest AI developments: Track frontier research, model architectures, training methods, post-training, inference systems, agents, world models, robotics, vision, and other emerging AI workloads. Translate relevant developments into NVIDIA opportunities.
  • Discover and define future workloads: Identify the next workloads, use cases, and technical requirements that will shape AI infrastructure. Engage early—before architectures, interfaces, and platform decisions are fixed.
  • Drive platform integration: Help partners adopt and optimize NVIDIA GPUs, systems, networking, and software libraries across their development pipelines (e.g., CUDA, CUDA-X, NCCL, TensorRT-LLM, NeMo, Transformer Engine, CUTLASS, vLLM, SGLang).
  • Influence NVIDIA’s platform roadmap: Communicate partner requirements, identify cross-lab patterns, and influence improvements from silicon through systems, libraries, frameworks, and scalable serving.
  • Support technical assessment of new AI labs: Work with Corporate Development, NVentures, VC Alliances, and other teams to assess capabilities, infrastructure needs, relevance, and collaboration potential.
  • Develop collaboration strategies: Define technical objectives, integration plans, milestones, success criteria, and partner roadmaps; draft technical collaboration agreements in partnership with NVIDIA teams.
  • Celebrate joint success: Partner with Marketing, Events, Communications, and PR to showcase collaborations through GTC, blogs, product announcements, case studies, panels, demos, and other activities.

Qualifications

  • B.S. degree or equivalent experience; an advanced degree in computer science, electrical engineering, machine learning, or related field preferred.
  • 8+ years of experience in AI research, AI infrastructure, distributed systems, GPU computing, technical product management, or engineering.
  • Current understanding of frontier AI research, model development, training, post-training, inference, and emerging AI workloads.
  • Practical understanding of GPU platforms and AI software libraries (CUDA, CUDA-X, NCCL, PyTorch or JAX) and related training or inference systems.
  • Experience with large-scale GPU clusters, high-speed networking, distributed storage, workload orchestration, performance optimization, and cloud or on-premises infrastructure.
  • Ability to understand complex model-builder architectures and translate into actionable engineering and product requirements.
  • Excellent written and verbal communication skills; ability to explain complex technical subjects to technical and non-technical audiences.
  • Ability to operate across NVIDIA Product, Engineering, Sales, Marketing, Events, PR, Corporate Development, NVentures, and executive teams.

Skills

Required:Technical engagement leadershipAI/ML frontier developmentsGPU platforms & libraries

Benefits

  • Join a pivotal role in NVIDIA’s Generative AI growth with opportunities for professional growth and impact across frontier labs and product development.
Last updated Sep 18, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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