At a Glance
- Tasks: Lead technical engagements with top AI labs and drive platform integration.
- Company: Join NVIDIA, a leader in AI technology and innovation.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Dynamic environment with a startup mindset and rapid expansion in Generative AI.
- Why this job: Shape the future of AI while working with cutting-edge technologies and top researchers.
- Qualifications: 8+ years in AI research or infrastructure; strong technical and communication skills required.
The predicted salary is between 72000 - 88000 £ per year.
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 revolutionise 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.
Tech Engagement Lead, AI Labs - EMEA employer: NVIDIA Corporation
NVIDIA stands out as an exceptional employer, offering a dynamic work environment that fosters innovation and collaboration among talented professionals. With a strong commitment to diversity and inclusion, employees benefit from competitive salaries, comprehensive benefits, and ample opportunities for personal and professional growth, all while contributing to groundbreaking advancements in AI and technology. Joining NVIDIA means being part of a mission-driven team that values creativity and empowers individuals to make a significant impact in the tech industry.
StudySmarter Expert Advice🤫
We think this is how you could land Tech Engagement Lead, AI Labs - EMEA
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at NVIDIA Corporation or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to NVIDIA Corporation.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like NVIDIA Corporation.
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We think you need these skills to ace Tech Engagement Lead, AI Labs - EMEA
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at NVIDIA Corporation.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at NVIDIA Corporation and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at NVIDIA Corporation
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If NVIDIA Corporation uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.