Senior GPU Kernel Developer

Luxoft; Ciudad de México; Presencial; MXN 738,000 - 1,108,000; Jornada completa

Descripción de la vacante

A technology firm in Mexico City is seeking an experienced developer to optimize GPU applications using CUDA or HIP frameworks. The ideal candidate should have a solid background in C++ programming, parallel programming, and performance profiling. Responsibilities include leading the optimization of HIP kernels on AMD GPUs and collaborating with teams to enhance application performance. This role offers an opportunity to work with the latest advancements in GPU technologies.

Formación

• Proficiency with C++ and low-level programming.
• Proficiency in CUDA or HIP / ROCm programming.
• Solid understanding of GPU architectures and optimization techniques.
• Strong problem-solving skills.

Responsabilidades

• Help optimize HIP kernels for specific AMD hardware.
• Collaborate with development teams to enhance GPU-accelerated applications.
• Debug, profile, and fine-tune code for performance improvements.

Conocimientos

C++ (at least C++ 17)

CUDA or HIP / ROCm programming

GPU architectures understanding

Parallel programming models

Problem-solving skills

Python

Experience in AI/ML/DL/NN/NLP/Computer Vision

Herramientas

Linux

Profiling tools

gdb/LLDB

Descripción del empleo

Project description

Luxoft is searching for talented developers with GPU compute and performance profiling experience to join the rapidly growing team. We are seeking an experienced individual proficient in GPGPU applications to join our team. The primary responsibility of this role will be to lead the effort in optimizing HIP kernels on AMD GPUs. The candidate should possess a strong background in GPU computing, parallel programming, and a deep understanding of CUDA or HIP frameworks. Additionally, familiarity with optimization techniques is highly desirable.

Responsibilities

• The main task will be to help optimize HIP kernels for specific AMD hardware
• Collaborate with development teams to optimize and enhance GPU-accelerated applications
• Debug, profile, and fine-tune code for performance improvements
• Stay updated with the latest advancements in GPU architectures and programming models

SKILLS

Must have

• Proficiency with C++ and low-level programming (at least C++ 17)
• Proficiency in CUDA or HIP / ROCm programming
• Solid understanding of GPU architectures, parallel programming models, and optimization techniquesStrong problem-solving skills and the ability to work in a collaborative environment
• One of AI/ML/DL/NN/NLP/Computer Vision experience
• Python

Nice to have

• Linux
• CPU Intrinsics (AVX/SSE)
• GPU Assembler
• Profiling
• gdb/LLDB
• Jinja2 or similar templating engines