AI Compiler Optimization Engineer

Salary: £100,000 - 100,000 per year

Requirements:

• Experience with compiler techniques to improve AI model inference performance on CPU or CPU/XPU hybrid systems
• Experience with LLVM/MLIR development is preferred
• Experience profiling and optimizing AI frameworks such as TensorFlow, PyTorch, ONNX, and llama.cpp is preferred
• Strong technical writing skills with prior publications or reports are preferred

Responsibilities:

• We implement compiler-based performance optimizations to improve inference latency and throughput on CPU and CPU/XPU hybrid systems
• We optimize JIT-level compute graphs through operator fusion, memory allocation, and related techniques
• We profile end-to-end inference workflows to identify hotspots and bottlenecks in AI frameworks such as TensorFlow, PyTorch, ONNX, and llama.cpp
• We propose and implement optimization strategies such as kernel tuning and graph-level optimizations
• We track and analyze the latest advancements in AI and compiler research, including academic papers and open-source projects
• We produce actionable insight reports summarizing trends, benchmarks, and potential optimizations

Technologies:

• AI
• LLVM
• PyTorch
• TensorFlow
• Backend

More:

We are seeking a skilled AI Compiler Optimization Engineer to help us optimize AI model inference performance through advanced compiler technologies. In this role, we focus on performance tuning for CPU and hybrid CPU/XPU heterogeneous architectures, profiling AI frameworks to uncover new optimization opportunities, and turning industry research into practical insights.

last updated 34 week of 2026