C++ Developer - CUDA, Kernel, Tensorrt, GPU

Dcoded; England; Remote; GBP 50,000 - 70,000; Full time

Job summary

A tech company is seeking an experienced CUDA Backend Developer to join their engineering team working on GPU-accelerated projects. Responsibilities include designing and implementing CUDA kernels, optimizing GPU performance, and collaborating with researchers. Strong experience in C++ and CUDA C is required, along with skills in GPU profiling and Linux systems development. This role offers a remote working option within the UK or EU.

Qualifications

• 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.

Responsibilities

• Design and implement GPU kernels in CUDA C, focusing on kernel fusion and on-device operations.
• Optimize custom models for deployment with TensorRT or similar inference engines.
• Integrate GPU functionality into Back End APIs and orchestration layers.

Skills

C++ programming

CUDA C programming

GPU optimization

Multi-threaded architectures

Linux systems development

Performance tuning

Tools

Nsight

Docker

Kubernetes

Job description

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.