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- Tasks: Design and optimise CUDA kernels for high-performance AI applications.
- Company: Join a cutting-edge tech company focused on GPU-accelerated software.
- Benefits: Remote work, competitive pay, and the chance to shape emerging AI technology.
- Other info: Opportunity to work in a fast-paced, impactful environment.
- Why this job: Be part of a low-ego team solving complex performance challenges.
- Qualifications: Experience with CUDA C/C++ and a passion for high-performance computing.
The predicted salary is between 36000 - 60000 ÂŁ per year.
CUDA Developer | High-Performance Computing | Applied AI
Location: UK-based Remote
Type: Contract, Outside IR35, Remote
Sector: Advanced Computing / Applied AI
We’re partnering with a company building next-generation GPU-accelerated software for scientific and AI applications. We are recruiting for a CUDA Developer who’s passionate about getting every ounce of performance out of modern hardware — someone who loves tuning kernels, benchmarking workloads, and finding elegant solutions to complex computational problems.
This is an opportunity to work with a small, expert team where your technical decisions will shape the foundation of an emerging AI technology.
What You’ll Be Doing
- Designing and optimising CUDA kernels for high-performance workloads.
- Translating advanced algorithms into production-ready GPU-accelerated code.
- Profiling performance and reducing bottlenecks using Nsight, CUPTI, and custom tooling.
- Working with C++ engineers and ML researchers to deliver scalable AI computation pipelines.
- Contributing to architecture decisions on parallelisation, data transfer, and memory efficiency.
What We’re Looking For
- Deep experience with CUDA C/C++ and modern C++ (17/20).
- Strong understanding of GPU architecture, memory management, and parallelism.
- Familiarity with OpenMP, MPI, or other HPC frameworks.
- Bonus points for exposure to AI/ML workloads or scientific computing.
- Pragmatic and collaborative — you enjoy working in fast-moving, high-impact environments.
Why This Role?
You’ll be part of a technically elite, low-ego team solving problems at the cutting edge of performance engineering. Your work will be deeply visible. The difference between “it works” and “it flies”. If you love performance, parallelism, and precision, then please apply with a current CV for more information.
Software Engineer employer: Silicon Fen Resourcing
Contact Detail:
Silicon Fen Resourcing Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your CUDA projects or any relevant work. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your CUDA knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for passionate developers like you, and applying directly can give you a better chance of standing out.
We think you need these skills to ace Software Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with CUDA C/C++ and modern C++. We want to see how you've tackled performance challenges and optimised workloads, so don’t hold back on those details!
Showcase Your Projects: Include any relevant projects that demonstrate your skills in high-performance computing and AI. Whether it's tuning kernels or working with ML researchers, we love seeing practical examples of your work.
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language to explain your experience and how it aligns with the role. We appreciate a well-structured application that gets straight to the point!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. We can’t wait to hear from you!
How to prepare for a job interview at Silicon Fen Resourcing
✨Know Your CUDA Inside Out
Make sure you brush up on your CUDA C/C++ skills before the interview. Be prepared to discuss your experience with designing and optimising CUDA kernels, as well as any specific projects where you've tackled performance issues. Having concrete examples ready will show your passion for high-performance computing.
✨Understand GPU Architecture
Familiarise yourself with GPU architecture and memory management concepts. You might be asked technical questions about how to reduce bottlenecks or improve parallelism. Being able to explain these concepts clearly will demonstrate your deep understanding of the technology.
✨Showcase Your Problem-Solving Skills
Prepare to discuss complex computational problems you've solved in the past. Think about how you translated advanced algorithms into production-ready code and the impact it had on performance. This will highlight your ability to find elegant solutions in a fast-paced environment.
✨Collaborate and Communicate
Since this role involves working closely with C++ engineers and ML researchers, be ready to talk about your collaborative experiences. Share examples of how you've contributed to architecture decisions or worked in teams to deliver scalable AI computation pipelines. This will show that you're not just a tech whiz but also a team player.