Senior Solutions Architect – Large Scale Neural Networks Inference

Senior Solutions Architect – Large Scale Neural Networks Inference

Full-Time 72000 - 88000 £ / year (est.) Hybrid
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At a Glance

  • Tasks: Lead AI inference strategy and optimise high-performance pipelines for cutting-edge projects.
  • Company: Join NVIDIA, a leader in AI technology with a diverse and inclusive culture.
  • Benefits: Competitive salary, comprehensive benefits, and opportunities for professional growth.
  • Other info: Work in a dynamic environment with excellent career advancement opportunities.
  • Why this job: Make a real impact in the AI field while working with top-tier technology.
  • Qualifications: MS/PhD in Computer Science or Engineering with 8+ years in AI/ML infrastructure.

The predicted salary is between 72000 - 88000 £ per year.

We are seeking a Senior Solutions Architect with deep expertise in large-scale neural network inference and a proven ability to lead technical collaboration with frontier AI labs and enterprises deploying AI at scale across EMEA.

In this role, you will define the technical direction for AI inference across EMEA by identifying critical bottlenecks and driving the development of scalable, high-impact solutions.

By aligning key team members within NVIDIA and customer organizations, you will influence strategic technology decisions to develop the deployment of next-generation AI inference at scale.

  • What You Will Be Doing
  • Lead the inference strategy for a portfolio of EMEA AI Natives customers, guiding engagements from initial proof of concept to production-scale deployments.
  • Identify inference challenges across customer deployments including latency, efficiency, cost per token, memory utilization, and low-latency networking.
  • Architect and optimize high-performance inference pipelines using NVIDIA Dynamo, Tensor RT-LLM, v LLM, SGLang, and other inference backends, improving GPU utilization and AI cluster efficiency.
  • Translate customer insights and deployment patterns into actionable product feedback that develops the roadmap for NVIDIA stack such as Dynamo, Tensor RT-LLM, and NIM.
  • What We Need To See
  • MS or Ph D in Computer Science, Engineering, or equivalent experience in the field.
  • 8+ years in AI/ML infrastructure, with deep expertise in LLM/VLM inference optimization and production deployment at scale.
  • Deep understanding of transformer inference acceleration: quantization (INT4/FP8), speculative decoding, disaggregated inference, continuous batching, KV cache optimization, and Wide EP for Mo E models.
  • Understanding of GPU memory hierarchies and low-latency networking along with their influence on inference performance.
  • Proven track record to lead technical initiatives.
  • Excellent communication skills, effective with research scientists, infrastructure engineers, and executive team members.
  • Ways To Stand Out From The Crowd
  • Experience with NVIDIA's inference stack, including Tensor RT-LLM, Triton Inference Server, NIM, and NVIDIA Dynamo.
  • Experience with GPU orchestration on Kubernetes.
  • You have operated inference at scale inside a frontier AI lab or hyperscale's inference team.
  • Contributions to open-source inference projects such as v LLM, SGLang, KServe, or NVIDIA Dynamo.

Widely considered to be one of the technology world's most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package.

As you plan your future, see what we can offer www. nvidiabenefits. com/

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer.

As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

For

Poland: The base salary range is 292,500 PLN - 507,000 PLN for Level 4, and 375,000 PLN - 650,000 PLN for Level 5. , , JR2024432

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Senior Solutions Architect – Large Scale Neural Networks Inference employer: Nvidia

NVIDIA is a leading innovator in the tech industry, renowned for its commitment to fostering a diverse and inclusive work environment where creativity thrives. As an AI Natives Sales Account Manager, you'll benefit from competitive salaries, comprehensive benefits, and unparalleled opportunities for professional growth while working at the forefront of AI technology in the UK. Join us to make a meaningful impact and be part of a team that values your contributions and encourages innovation.

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Contact Details:

Nvidia Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Solutions Architect – Large Scale Neural Networks Inference

✨Join Local Tech Meetups

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✨Contribute to Open Source Projects

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We think you need these skills to ace Senior Solutions Architect – Large Scale Neural Networks Inference

Large-Scale Neural Network Inference
Technical Collaboration
AI Inference Strategy
Latency Optimization
Cost Efficiency Analysis
Memory Utilization
Low-Latency Networking

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.

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 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

✨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 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.