Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and optimise GPU kernels in CUDA C for high-performance AI workloads.
- Company: Join a dynamic engineering team pushing the limits of GPU technology.
- Benefits: Competitive daily rate, remote work, and potential for contract extension.
- Why this job: Be at the forefront of AI innovation and tackle complex backend challenges.
- Qualifications: Strong C++ and CUDA experience with a passion for GPU performance.
- Other info: Remote role with opportunities for growth in cutting-edge tech.
C++ / CUDA Backend Developer – Contract
Remote | £400-£500 per day | Outside IR35 | 6-Month Initial Engagement
Overview
We\’re looking for an experienced CUDA Backend Developer to join a high-performance engineering team working on GPU-accelerated simulation and AI workloads. You\’ll collaborate with C++ systems engineers and research scientists to design, implement, and optimize GPU-intensive Back End modules that push the limits of performance and scalability.
What You\’ll Do
- Design and implement GPU kernels in CUDA C, focusing on:
- Kernel fusion
- On-device operations
- GPU memory optimization
- Build and use profiling tools (eg, Nsight) to measure and improve GPU utilization, inference latency, and training throughput.
- Optimize custom models for deployment with TensorRT or similar inference engines.
- Integrate GPU functionality into Back End APIs and orchestration layers.
- Work closely with research and engineering teams to translate models into performant CUDA implementations.
What We\’re Looking For
- Strong experience in C++ (11/14/17) and CUDA C programming.
- Proven track record using GPUs for compute-intensive applications in production environments.
- Hands-on with CUDA profiling, debugging, and Kernel optimization.
- Deep understanding of multi-threaded/multi-process architectures and Linux systems development.
- Proficiency in low-level I/O, memory management, and performance tuning
Nice to Have
- Experience with distributed training/inference pipelines.
- Familiarity with Docker and Kubernetes.
- Exposure to Embedded systems or hardware-level software integration.
Start: ASAP
Duration: 6 months (strong potential to extend)
Location: Remote (UK or EU-based preferred)
IR35: Outside
If you\’re a GPU performance enthusiast who thrives on complex Back End challenges and wants to contribute to cutting-edge AI systems, we\’d love to hear from you.
Apply now or get in touch directly for a confidential conversation.
C++ Developer employer: dcoded. | B Corp ™ pending
Contact Detail:
dcoded. | B Corp ™ pending Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land C++ Developer
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech world, especially those who work with C++ or CUDA. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a GitHub repository showcasing your C++ and CUDA projects. 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 related to GPU optimization and multi-threading to impress during the interview.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from passionate developers like you!
We think you need these skills to ace C++ Developer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with C++ and CUDA specifically. We want to see how you've tackled GPU-intensive applications, so don’t hold back on those details!
Showcase Your Projects: Include any relevant projects or experiences that demonstrate your skills in GPU memory optimization and kernel fusion. We love seeing real-world applications of your expertise!
Be Clear and Concise: When writing your cover letter, keep it straightforward. We appreciate clarity, so get straight to the point about why you’re a great fit for our team and what you can bring to the table.
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.
How to prepare for a job interview at dcoded. | B Corp ™ pending
✨Know Your C++ and CUDA Inside Out
Make sure you brush up on your C++ (11/14/17) and CUDA C skills before the interview. Be ready to discuss specific projects where you've implemented GPU kernels, optimised memory usage, or tackled performance issues. Having concrete examples will show your expertise and make you stand out.
✨Familiarise Yourself with Profiling Tools
Get comfortable with profiling tools like Nsight. During the interview, you might be asked how you've used these tools to measure GPU utilisation or improve inference latency. Being able to talk about your hands-on experience with these tools will demonstrate your practical knowledge.
✨Understand the Bigger Picture
It's not just about coding; understand how your work fits into the larger system. Be prepared to discuss how you would integrate GPU functionality into Back End APIs and orchestration layers. Showing that you can think beyond just the code will impress your interviewers.
✨Prepare for Technical Questions
Expect technical questions related to multi-threaded architectures, memory management, and performance tuning. Brush up on these topics and be ready to solve problems on the spot. Practising common interview questions in these areas can help you feel more confident.
