Senior Software Development Engineer in England

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.

About The Role

We are seeking an experienced and highly technical SMTS Software Development Engineer to drive the design, development, optimization, and maintenance of the HIP runtime, a core component of the ROCm software stack. In this role, you will contribute to the evolution of HIP as a high‑performance C++ GPU programming environment, enabling developers to write portable, efficient GPU applications for AMD GPUs targeting data‑center, cloud, and AI workloads. This position requires deep understanding of GPU programming models, runtime systems, compiler interfaces, and systems‑level performance engineering.

Key Responsibilities

• HIP Runtime Development
  • Architect, implement, and optimize features in the HIP runtime, including memory management, kernel dispatch, device abstraction, multi‑GPU coordination, and synchronization primitives.
  • Contribute to the evolution of the HIP programming model and interoperability with ROCr, HSA runtime, and compiler toolchains.
  • Ensure functional correctness, performance, and scalability of runtime APIs across different GPU generations.
• Performance & Systems Engineering
  • Conduct root‑cause analysis and systems‑level debugging across the runtime, driver, compiler, and hardware layers.
  • Profile GPU applications and internal runtime components to identify bottlenecks and design performance improvements.
  • Optimize HIP runtime behavior for large‑scale AI, HPC, and cloud workloads.
• Cross‑Component Collaboration
  • Work closely with compiler teams (LLVM/Clang), driver teams, GPU architecture, and systems engineers to deliver end‑to‑end GPU software solutions.
  • Contribute to API specifications and collaborate with upstream open‑source communities where appropriate.
• Quality, Reliability & Testing
  • Define and drive technical strategy for correctness, reliability, and conformance of the HIP runtime.
  • Support enhancements in automated testing, CI, and stress/failure scenarios in the HIP test suite.
  • Review design proposals, code reviews, and technical documents for quality and architectural alignment.
• Technical Leadership
  • Mentor junior engineers and contribute to establishing best practices in systems software development.
  • Evaluate complex technical tradeoffs and drive decisions in runtime design and optimization.
  • Represent the HIP runtime in technical discussions across ROCm teams and with strategic partners.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or related technical field.
• 8+ years of software engineering experience in systems software, runtime libraries, GPU programming, or compiler/runtime interfaces.
• Strong proficiency in modern C++ (C++14/C++17 or newer), templates, memory models, and low‑level systems programming.
• Deep understanding of at least one GPU computing model (HIP, CUDA, SYCL, OpenCL, OpenMP offload).
• Hands‑on experience with runtime systems, driver interfaces, or high‑performance compute libraries.
• Strong debugging skills using tools such as gdb, sanitizers, profilers, and GPU debugging tools.
• Solid understanding of parallel programming concepts—memory hierarchy, synchronization, concurrency, thread scheduling.

Preferred Qualifications

• Experience contributing to ROCm, HIP, CUDA runtime, or similar GPU programming runtimes.
• Familiarity with LLVM/Clang, compiler toolchains, and code generation pipelines.
• Experience with multi‑GPU systems, distributed execution frameworks, or heterogeneous memory systems.
• Background in HPC, AI/ML frameworks, or performance tuning for GPU workloads.
• Prior contributions to large‑scale open‑source projects.
• Experience with Linux systems programming, POSIX APIs, and low‑level debugging.