At a Glance
- Tasks: Optimise AI model performance using advanced compiler technologies and profiling techniques.
- Company: Join Huawei, a global leader in ICT with a commitment to innovation.
- Benefits: Enjoy 33 days of annual leave, private medical insurance, and a pension scheme.
- Other info: Dynamic work environment with opportunities for learning and development.
- Why this job: Make a real impact in AI and compiler optimisation while working with cutting-edge technology.
- Qualifications: Proficient in C/C++ with experience in AI frameworks and performance profiling tools.
The predicted salary is between 63000 - 77000 £ per year.
About Huawei Research and Development UK Limited. Founded in 1987, Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. We have 207,000 employees and operate in over 170 countries and regions, serving more than three billion people around the world. Our vision and mission is to bring digital to every person, home and organization for a fully connected, intelligent world.
Huawei’s vision is a fully connected, intelligent world. To achieve this, we work to inspire passion for basic research around the world. Our combined passion drives development across the global innovation value chain. Huawei has the largest Research and Development organization in the world with 96,000+ employees in research centers around the globe. In the UK, we already have design centers in Cambridge, London, Edinburgh and Ipswich.
We invite you to join us on this exciting journey and drive your career forward.
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 and 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.
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.
AI Compiler Optimization Engineer in Cambridge employer: Huawei R&D UK
Huawei Research and Development UK Limited is an exceptional employer, offering a dynamic work environment in Edinburgh that fosters innovation and collaboration. With a strong focus on employee growth, the company provides extensive benefits including generous annual leave, private medical insurance, and opportunities for professional development through partnerships with leading academic institutions. Joining Huawei means being part of a global leader in ICT, where your contributions can directly impact the future of data management and AI technologies.
StudySmarter Expert Advice🤫
We think this is how you could land AI Compiler Optimization Engineer in Cambridge
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Huawei R&D UK or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
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We think you need these skills to ace AI Compiler Optimization Engineer in Cambridge
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Huawei R&D UK.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Huawei R&D UK and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Huawei R&D UK
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Huawei R&D UK uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
