Senior GPU Kernel Developer

Luxoft; United States; Remote; USD 80,000 - 100,000; Full time

Job summary

An established industry player is on the lookout for talented developers to join their dynamic team. This role focuses on optimizing HIP kernels on AMD GPUs, requiring a strong background in GPU computing and parallel programming. If you have expertise in CUDA or HIP frameworks, along with proficiency in C/C++ and Python, this opportunity is perfect for you. Collaborate with development teams, debug and profile code, and stay updated with the latest advancements in GPU architectures. Join a rapidly growing team where your contributions will significantly impact cutting-edge projects in the tech landscape.

Qualifications

• Proficient in CUDA or HIP with strong GPGPU programming skills.
• Experience in C/C++ and Python with a focus on performance optimization.

Responsibilities

• Optimize HIP kernels for specific AMD hardware and enhance GPU-accelerated applications.
• Debug, profile, and fine-tune code for performance improvements.

Skills

CUDA

HIP

GPGPU programming

C/C++ (C++17 or later)

Python

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

Optimization techniques

Problem-solving skills

Tools

gdb

LLDB

Linux

Jinja2

Job description

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

• CUDA or HIP.
• GPGPU programming proficiency.
• C/C++ (C++17 or later).
• Python.
• One of AI/ML/DL/NN/NLP/Computer Vision experience.
• Mandatory Skills Description: Proficiency with C++ and low-level programming.
• Proficiency in CUDA or HIP / ROCm programming.
• Solid understanding of GPU architectures, parallel programming models, and optimization techniques.
• Strong problem-solving skills and the ability to work in a collaborative environment.

Nice to have

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