Key Responsibilities
- As a Senior Software Engineer in the AI Processor Software & Hardware Co-design Lab, you will be responsible for designing and implementing both compile-time and run-time optimizations to enable real-time AI applications on Huawei AI processors. You will collaborate closely with cross-functional teams to integrate and deploy AI solutions on the Ascend platform, leveraging your expertise to shape the performance, functionality, and efficiency of our AI models and systems.
- Be responsible for one of the sub technical directions of AI Processor Software & Hardware Co-design Lab, identify key root technologies related to NPU chips, develop evolution strategies and roadmaps, promote and implement the evolution strategies to build industry-leading technical competitiveness, support Huawei's business success in the computing field.
- Carry out technology and business innovation, integrate several sub-domains of application algorithms, frameworks, runtime, modelling and simulation, and compilers from the perspective of processors, and build end-to-end architecture competitiveness.
- Grasp the AI industry and technology trends, gain insight into the development direction of AI applications and algorithms, develop key technical architectures of basic AI software and hardware, and resolve key usability and performance issues in full-stack AI through technical projects.
This job description is only an outline of the tasks, responsibilities and outcomes required of the role. The jobholder will carry out any other duties as may be reasonably required by his/her line manager. The job description and personal specification may be reviewed on an ongoing basis in accordance with the changing needs of Huawei Research and Development UK Limited.
Person Specification
- Required:
- Rich experience in optimizing AI chip architectures and AI systems, be familiar with mainstream heterogeneous computing software and hardware architectures in the industry, and have comprehensive capabilities from applications to basic software to chips.
- Hands‑on experience of one of the following technologies: Numerical Calculation, Compilation, Algorithm & chip co‑design, Runtime, Shared Memory.
- Knowledge of AI industry application scenarios, be familiar with mainstream models and algorithm development trends, and be able to extract requirements for the chip layer.
- Experience in analyzing workload sensitivity to micro‑architecture features, evaluating performance trade‑offs, and recommending improvements to both micro‑architecture and application software for optimal efficiency.
- Familiarity with the performance impact of different compute, memory, and communication configurations, as well as hardware and software implementation choices, on AI acceleration.
- Experience with GPU compute APIs such as CUDA or OpenCL, and the ability to utilize GPU/NPU‑optimized libraries to enhance performance.
- Experience in the development of deep learning frameworks, compilers, or system software.
- Strong background in compilers and optimization techniques; experience with LLVM‑MLIR is a plus, but not required.
- Experience in software development using C/C++ and Python.
- Desired:
- Relevant experience in several sub-fields of AI application algorithms, frameworks, runtime, modelling and simulation, and compilers.
- In‑depth understanding of the innovative methods, platforms, and tools of AI head manufacturers, and have experience in transforming application and academic research achievements into commercial products.
- Experience with GPU acceleration using AMD or Nvidia GPUs.
- Experience in developing inference backends and compilers for GPU or NPU.
- Experience with AI/ML inference frameworks like ONNXRuntime, IREE or TVM.
- Experience with deploying AI models in production environments.
What we offer
- 33 days annual leave entitlement per year (including UK public holidays)
- Group Personal Pension
- Life insurance
- Private medical insurance
- Medical expense claim scheme
- Employee Assistance Program
- Cycle to work scheme
- Company sports club and social events
- Additional time off for learning and development
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