Nokia
Nokia

SW Engineer – GPU & NVIDIA Platform Focus

RoleEmbedded
LevelSenior
LocationPortugal
WorkOn-site
TypeFull-time
Posted1 month ago
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About the role

As a Software Developer in our new **GPU-powered 5G Layer1 (L1)**team based in Amadora, you will play a crucial role in the development of CUDA-based embedded software that powers Nokia’s 5G base station products. You will work within specialized scrum teams, focusing on areas such as GPU feature implementation using C/C++ and CUDA, code optimization for NVIDIA architectures, and continuous integration. Collaborating with talented colleagues, you will address challenging problems that impact millions of end-users.

You have:

  • Several years of experience in GPU programming and CUDA development.
  • Proactive and independent with strong communication skills.
  • Fluency in English.
  • Understanding of LTE/5G systems and L1 technology area.

It would be nice if you also had:

  • Solid signal processing or physical layer processing experience on GPUs.

  • Strong background in managing product quality.

  • Understanding of Nokia RAN R&D and related product creation processes and tools.

  • Develop and implement high-performance GPU-accelerated embedded software for Nokia's 5G base station products focusing on Layer 1 (L1) functionality using CUDA and NVIDIA GPUs.

  • Collaborate within specialized scrum teams to optimize GPU code, enhance signal processing, and manage feature implementation.

  • Conduct feasibility studies on 3GPP 5G features and draft detailed technical requirements.

  • Lead planning and organization of tasks within global software development teams to ensure timely delivery.

  • Engage in system design and architecture with GPU acceleration, contributing to robust and efficient software infrastructure.

  • Oversee testing processes, including unit, component, and integration testing to maintain software quality.

  • Facilitate knowledge sharing and mentorship within the team, promoting continuous learning and professional growth.

  • Champion best practices in GPU-based DevOps, leveraging tools like Docker and Python for seamless integration and deployment.

Required skills

CUDA

GPU programming

C++

Embedded software

5G Layer 1

Code optimization

System design

Scrum collaboration

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