Job Summary
We are seeking a skilled AI Compiler Optimization Engineer to optimize AI model inference performance through advanced compiler technologies. You will focus on performance tuning for CPU or hybrid CPU/XPU heterogeneous architectures, profiling AI frameworks to discover new optimization opportunities, and delivering cutting‑edge insights from industry research.
Key Responsibilities
- Compiler-Based Performance Optimization
- Implement compiler techniques (e.g., MLIR level optimizations, LLVM backend optimizations) to enhance inference performance on CPU and CPU/XPU hybrid systems.
- Optimize JIT level compute graphs with operator fusion, memory allocation, etc. for latency/throughput improvements.
- Preferred: Experience with LLVM/MLIR development.
- AI Model Profiling & Framework Optimization
- Profile end-to-end inference workflows on frameworks like TensorFlow, PyTorch, ONNX, and llama.cpp to identify hotspots and bottlenecks.
- Propose and implement optimization strategies (e.g., kernel tuning, graph-level optimizations).
- Preferred: Experience optimizing models on multiple AI frameworks.
- Research & Insight Development
- Track and analyze the latest advancements in AI & compiler research (academic papers, open‑source projects).
- Produce actionable insight reports summarizing trends, benchmarks, and potential optimizations.
- Preferred: Strong technical writing skills with prior publications or reports.
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
- Proficiency in C/C++ and compiler infrastructure (LLVM, MLIR, or similar).
- Deep understanding of AI model architectures and inference workflows.
- Experience with performance profiling tools (e.g., perf, TensorBoard, VTune).
- Familiarity with CPU/XPU hardware architectures and optimization techniques.
- Strong analytical and problem‑solving skills.
- Desired
- BSc/MSc/MSci in CS
- Contributions to open‑source compiler projects (LLVM/MLIR communities).
- Experience with heterogeneous computing (CPU/GPU/XPU).
- Published work or technical blogs on AI/compiler optimization topics.
- Good at self‑learning, courageous to explore new things, strong in practical skill.
- Good teamwork and communication skills in both Mandarin and English.
What We Offer
- Assign with an industry expert as Mentor
- Fixed‑term employment contract up to two years
- Flexible working
- 33 days annual leave entitlement per year (including UK public holidays)
- Group Personal Pension
- Corporate retail discounts
- Employee Assistance Programme
- Life insurance
- Corporate social events
Job Summary
We are seeking a skilled AI Compiler Optimization Engineer to optimize AI model inference performance through advanced compiler technologies. You will focus on performance tuning for CPU or hybrid CPU/XPU heterogeneous architectures, profiling AI frameworks to discover new optimization opportunities, and delivering cutting‑edge insights from industry research.
Key Responsibilities
- Compiler-Based Performance Optimization
- Implement compiler techniques (e.g., MLIR level optimizations, LLVM backend optimizations) to enhance inference performance on CPU and CPU/XPU hybrid systems.
- Optimize JIT level compute graphs with operator fusion, memory allocation, etc. for latency/throughput improvements.
- Preferred: Experience with LLVM/MLIR development.
- AI Model Profiling & Framework Optimization
- Profile end-to-end inference workflows on frameworks like TensorFlow, PyTorch, ONNX, and llama.cpp to identify hotspots and bottlenecks.
- Propose and implement optimization strategies (e.g., kernel tuning, graph-level optimizations).
- Preferred: Experience optimizing models on multiple AI frameworks.
- Research & Insight Development
- Track and analyze the latest advancements in AI & compiler research (academic papers, open‑source projects).
- Produce actionable insight reports summarizing trends, benchmarks, and potential optimizations.
- Preferred: Strong technical writing skills with prior publications or reports.
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
- Proficiency in C/C++ and compiler infrastructure (LLVM, MLIR, or similar).
- Deep understanding of AI model architectures and inference workflows.
- Experience with performance profiling tools (e.g., perf, TensorBoard, VTune).
- Familiarity with CPU/XPU hardware architectures and optimization techniques.
- Strong analytical and problem‑solving skills.
- Desired
- BSc/MSc/MSci in CS
- Contributions to open‑source compiler projects (LLVM/MLIR communities).
- Experience with heterogeneous computing (CPU/GPU/XPU).
- Published work or technical blogs on AI/compiler optimization topics.
- Good at self‑learning, courageous to explore new things, strong in practical skill.
- Good teamwork and communication skills in both Mandarin and English.
What We Offer
- Assign with an industry expert as Mentor
- Fixed‑term employment contract up to two years
- Flexible working
- 33 days annual leave entitlement per year (including UK public holidays)
- Group Personal Pension
- Corporate retail discounts
- Employee Assistance Programme
- Life insurance
- Corporate social events
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