Overview

In this role you will help design, implement and optimize GNSS signal processing on a GPU-accelerated, distributed server platform. You will collaborate with cross-functional teams to shape the GNSS receiver software stack and its high‑performance execution. The role focuses on boosting performance, scalability, and reliability of GPU-accelerated pipelines in a space-oriented context. This is a hands-on, impact-focused opportunity to contribute to advanced GNSS solutions at scale.

Compensaciones / Ventajas

- Hybrid working model
- 8 weeks per year teleworking
- Flexible start and finish times
- Relocation package
- Health, dental and accident insurance
- Training and language learning support

Responsabilidades

- Support implementation and optimization of signal processing algorithms on GPUs
- Assist in designing distributed architectures for GNSS receivers




- Contribute to data transmission and synchronization mechanisms over high‑speed networks

Requisitos principales

- Parallel programming with CUDA
- Memory management, performance analysis and profiling
- Development of solutions for transmitting data over high‑speed networks (10GbE) using Xilinx FPGAs
- Software for distributed architectures deployed on containers
- Systems programming languages (C/C++ and/or Rust)

- CUDA parallel programming
- Xilinx FPGA-based high-speed network data transmission
- Distributed architectures and containers
- C/C++ and/or Rust
- GPU-accelerated signal processing
- High-speed networking (10GbE)

📌 Junior High-Performance Computing and GPU Development Engineer (Barcelona)
🏢 GMV
📍 Barcelona