Tech Engagement Lead, AI Labs - EMEA
NVIDIA is hiring a Tech Engagement Lead, AI Labs - EMEA for a remote role open to applicants in France. It pays €101k-€176k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
- This is listed as a remote role.
- The posting mentions vLLM, PyTorch and JAX among its tools and skills.
- Level classes it as a lead role.
- NVIDIA has 2,700+ other open roles on Level.
AI in this role
NVIDIA is seeking a technically strong Technical Engagement Lead to work with frontier AI labs and model builders. This role will deepen the integration of NVIDIA’s platform—from GPU architecture and systems to software libraries—into leading research, training, post-training, inference, and emerging AI workloads.
You will operate at the intersection of AI research, infrastructure, product strategy, and partner engagement. You will understand how model builders develop and scale their systems, identify opportunities to improve their performance on NVIDIA, and translate those insights into product influence, technical collaborations, and joint success.
What you will be doing:
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. This may include CUDA, CUDA-X, NCCL, TensorRT-LLM, NeMo, Transformer Engine, CUTLASS, vLLM, SGLang, and related technologies.
Influence NVIDIA’s platform roadmap: Work with NVIDIA hardware and software product teams to 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 cross-functionally with Corporate Development, NVentures, VC Alliances, and other NVIDIA teams to assess the technical capabilities, infrastructure needs, strategic relevance, and collaboration potential of emerging AI labs.
Develop collaboration strategies: Help define technical objectives, integration plans, milestones, success criteria, and partner-specific roadmaps. Draft technical collaboration agreements and related working documents in partnership with the appropriate NVIDIA teams.
Celebrate joint success: Partner with Marketing, Events, Communications, and PR to identify and develop opportunities to showcase successful collaborations through GTC, developer blogs, product announcements, case studies, panels, demos, and other public or partner-facing activities.
What we need to see:
B.S. degree or equivalent experience; an advanced degree in computer science, electrical engineering, machine learning, or a related research or technical field is 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, including CUDA, CUDA-X, NCCL, PyTorch or JAX, and relevant 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, identify technical bottlenecks, and translate them into actionable engineering and product requirements.
Excellent written and verbal communication skills, including the ability to explain complex technical subjects clearly to technical and non-technical audiences.
Ability to operate effectively across NVIDIA Product, Engineering, Sales, Marketing, Events, PR, Corporate Development, NVentures, and executive teams.
Ways to stand out from the crowd:
Hands-on experience with large language models, multimodal models, diffusion or video models, reinforcement learning, agents, world models, robotics, or other frontier workloads.
Experience working below the framework layer with CUDA kernels, communication libraries, compilers, memory movement, precision, or performance optimization.
A track record of turning research or infrastructure insights into product requirements, platform improvements, technical integrations, public technical content, or joint customer success.
Strong curiosity, sound technical judgment, and the ability to stay current as the AI landscape evolves.
Ability to thrive in a startup mindset and dynamic environment, adapting quickly to evolving AI landscapes.
This role is an opportunity to help frontier AI labs build their most ambitious systems on NVIDIA, while shaping the next generation of NVIDIA’s hardware and software platform. You will help discover new workloads, influence the platform, scale technical learning across model builders, and elevate the joint successes that demonstrate what NVIDIA and its partners can achieve together.
Join NVIDIA at a crucial time as we pioneer Generative AI growth. We are in the infancy stage of building and scaling our Generative AI business for large model development. This role offers a unique opportunity to join this rapid expansion. NVIDIA's hardware, systems, and software libraries are at the heart of this growth. They empower large model builders to revolutionize their operations with powerful AI capabilities. This is your chance to be a key member of a team that will shape the future of AI model development, working with the world's leading AI research labs and the most innovative technologies. Your contributions will directly impact the trajectory of our Generative AI success, making this an unparalleled opportunity for professional growth and significant impact.
How we rate this
Tech Engagement Lead, AI Labs - EMEA at NVIDIA rates 87 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a research question you investigated. What did you find?
- Walk me through how you've used vLLM in your day-to-day work.
- What are the limits of PyTorch that you've run into, and how did you work around them?
- What's a project where you used JAX hands-on?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: AI Research, vLLM, PyTorch, and JAX. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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