GPU Application Engineer

Advanced Micro Devices, Inc•Austin, TX

3d•Hybrid

About The Position

At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career. We are looking for a GPU application engineer to enable AMD GPU acceleration through HIP for applications that currently use CUDA backends, or that require a new HIP-based backend. This role is part of an ISV enablement engineering team and focuses on application-level GPU programming, performance tuning, and integration. THE PERSON: The ideal candidate is a highly self‑driven GPU application engineer who can be productive from day one within a complex, performance‑critical codebase. You have hands‑on experience developing and optimizing mature CUDA‑based applications, and you bring a pragmatic, engineering‑first mindset: knowing when to chase peak performance and when to favor clarity, portability, and long‑term maintainability. You work independently, stay organized while driving multiple parallel efforts, and communicate clearly with cross-functional teams, application developers, and stakeholders.

Requirements

Advanced software development experience, with significant experience in GPU programming
Strong C/C++ programming skills
Hands-on experience with CUDA (kernel development, memory management, streams/events)
Experience developing GPU-accelerated applications
Solid understanding of GPU programming fundamentals
Strong debugging skills for GPU kernels and application pipelines
Experience developing on Linux

Nice To Haves

Experience with HIP and ROCm
Experience porting CUDA code to HIP (manual or hipify-based)
Familiarity with HIPRT or GPU ray tracing concepts
Experience with GPU profiling tools
Experience working in large, multi-backend codebases
Familiarity with NVIDIA OptiX or similar GPU ray tracing APIs

Responsibilities

Port CUDA-based GPU code to HIP, including kernels, runtime logic, and build systems
Design and implement HIP backends for applications without existing AMD GPU support
Enable and integrate HIP ray tracing (HIPRT) where applicable
Optimize GPU kernels and application pipelines for AMD GPU architectures
Debug correctness, performance, and stability issues in application-level GPU code
Work with profiling tools to identify and resolve bottlenecks
Collaborate with internal compiler/runtime teams to escalate lower-level issues when needed
Maintain clean, portable GPU code across vendors