Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop and optimise MLIR-based compiler components for cutting-edge AI workloads.
- Company: Join Axelera AI, a pioneering deep-tech startup transforming the AI landscape.
- Benefits: Attractive compensation, pension plan, employee insurances, and company shares.
- Other info: Flexible working arrangements and a commitment to diversity and inclusion.
- Why this job: Make a real impact in AI technology while collaborating with top experts across Europe.
- Qualifications: Master’s or PhD in Computer Science, with experience in AI frameworks and compiler design.
The predicted salary is between 60000 - 80000 £ per year.
About Us
Axelera AI is not your regular deep-tech startup. We are creating the next-generation AI platform to support anyone who wants to help advancing humanity and improve the world around us. In just four years, we have raised a total of $370 million and have built a world-class team of 220+ employees (including 49+ PhDs with more than 40,000 citations), both remotely from 18 different countries and with offices in Belgium, France, Switzerland, Italy, the UK, headquartered at the High Tech Campus in Eindhoven, Netherlands. We have also launched our Metisâ„¢ AI Platform, which achieves a 3-5x increase in efficiency and performance, and have visibility into a strong business pipeline exceeding $100 million. Our unwavering commitment to innovation has firmly established us as a global industry pioneer.
Position Overview
We are looking for a Frontend / Graph-level Compiler Engineer to join our growing compiler team at Axelera AI. In this role, you will play a key part in developing and optimizing our MLIR-based compiler stack, enabling efficient execution of AI workloads on cutting-edge heterogeneous hardware architectures. You will work closely with AI researchers, compiler engineers, and hardware architects, collaborating with a talented team of engineers across Europe. This is your chance to work on cutting-edge AI acceleration architectures, advance compiler technology, and make a real impact in a fast-moving startup environment.
Key responsibilities:
- Design, implement, and maintain frontend and graph-level compiler components using MLIR
- Develop and optimize graph-level transformations such as operator fusion, constant folding, operator sinking, graph partitioning, and other performance-critical optimizations
- Extend and maintain MLIR dialects, passes, and infrastructure to support AI workloads
- Integrate and lower AI models from frameworks such as PyTorch, ONNX, and TensorFlow into internal compiler representations
- Collaborate with hardware and backend compiler teams to ensure efficient mapping of AI workloads to heterogeneous architectures
- Support and mentor team members in adopting and effectively using MLIR infrastructure
- Analyze model graphs and implement optimizations to improve performance, memory efficiency, and execution efficiency
- Contribute to the design and evolution of the overall compiler architecture and tooling
- Debug, profile, and improve compiler performance and correctness
Qualifications:
- Master’s or PhD in Computer Science or a related technical field
- 3-5 years of experience in a Software Engineering role, thereof ideally 2 years of experience with Deep Learning frameworks and AI systems
- Experience with MLIR, including dialects, passes, and compiler infrastructure
- Solid understanding of compiler design principles and intermediate representations, especially graph-based IRs
- Experience working with AI model frameworks such as PyTorch (preferred), ONNX, or TensorFlow
- Proven experience implementing graph-level optimizations such as operator fusion, constant folding, graph partitioning, or similar transformations
- Strong programming skills in C++ and Python
- Experience working in collaborative engineering teams
- Excellent communication skills and willingness to share knowledge and mentor others
Nice to have:
- Experience working with custom AI accelerators or specialized hardware
- Background in computer architecture, especially heterogeneous systems (e.g., CPU + NPU, GPU, or dedicated accelerators)
- Experience with AI compiler stacks such as Torch-MLIR, TVM, XLA, Glow, or similar
- Experience optimizing AI workloads for performance and efficiency
- Familiarity with frontend model ingestion, graph lowering, and compiler pipelines
Location
We offer a flexible working arrangement, with options to:
- Work from one of our Axelera AI offices (Leuven in Belgium, Amsterdam and Eindhoven in the Netherlands, Zurich in Switzerland, Florence and Milan in Italy or Bristol in the United Kingdom) if you're already based in the vicinity.
- Work fully remotely from any European country (incl. the UK) you are already in.
- Relocate with us and work from Italy (Florence or Milan) or the Netherlands (Amsterdam or Eindhoven).
Kindly note that priority will be given to candidates who are [interested in being] based in Belgium or Italy.
What we offer
This is your chance to shape and be part of a dynamic, fast-growing, international organization. We offer an attractive compensation package, including a pension plan, extensive employee insurances and the option to get company shares. An open culture that supports creativity and continual innovation is awaiting you. Collaborative ownership and freedom with responsibility is characteristic for the way we act and work as a team. At Axelera AI, we wholeheartedly embrace equal opportunity and hold diversity in the highest regard. Our steadfast commitment is to cultivate a warm and inclusive environment that empowers and celebrates every member of our team. We welcome applicants from all backgrounds to join us in shaping the future of AI.
Senior AI Graph Compiler Engineer - MLIR Expert employer: Axelera AI
Contact Detail:
Axelera AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior AI Graph Compiler Engineer - MLIR Expert
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Axelera AI. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! If you’ve got a project or a portfolio that highlights your experience with MLIR or AI frameworks, make sure to share it during interviews or networking events.
✨Tip Number 3
Prepare for technical interviews by brushing up on compiler design principles and graph-level optimisations. We want to see how you think and solve problems, so practice coding challenges related to these topics.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Senior AI Graph Compiler Engineer - MLIR Expert
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Senior AI Graph Compiler Engineer. Highlight your experience with MLIR, deep learning frameworks, and any relevant projects that showcase your skills in compiler design and optimisations.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a perfect fit for our team. Don’t forget to mention specific experiences that relate to the job description.
Showcase Your Projects: If you've worked on any projects related to AI compilers or graph-level optimisations, make sure to include them. We love seeing real-world applications of your skills, so don’t hold back!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows us you’re serious about joining our innovative team at Axelera AI.
How to prepare for a job interview at Axelera AI
✨Know Your MLIR Inside Out
Make sure you have a solid grasp of MLIR and its components. Brush up on dialects, passes, and the overall compiler infrastructure. Be ready to discuss how you've used these in past projects, especially in relation to AI workloads.
✨Showcase Your Optimisation Skills
Prepare examples of graph-level optimisations you've implemented, like operator fusion or constant folding. Be specific about the challenges you faced and how your solutions improved performance or efficiency.
✨Collaborate Like a Pro
Since this role involves working closely with AI researchers and hardware architects, think of instances where you've successfully collaborated in a team. Highlight your communication skills and willingness to mentor others, as these are key in a fast-paced environment.
✨Understand the Bigger Picture
Familiarise yourself with Axelera AI's mission and the impact of their technology. Be prepared to discuss how your role as a Frontend/Graph-level Compiler Engineer fits into their vision for advancing AI and improving the world.