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- Tasks: Architect and develop cutting-edge distributed systems for AI and data-centric workloads.
- Company: Join Huawei's innovative Edinburgh Research Centre, shaping the future of AI infrastructure.
- Benefits: Competitive salary, opportunities for research publications, and a collaborative work environment.
- Why this job: Be at the forefront of AI technology and make a real impact in the industry.
- Qualifications: Bachelor's or Master's in Computer Science or related field; strong knowledge of distributed systems.
- Other info: Dynamic team with opportunities for career growth and cross-team collaboration.
The predicted salary is between 36000 - 60000 £ per year.
In an era where LLM are rebuilding the foundational software stack, Huawei's CloudMatrix super-node clusters and AI-native infrastructure are reshaping how large-scale models are trained, served, and deployed. The Edinburgh Research Centre plays a key role in this transformation, driving new AI Infra & Agentic Serving architectures and helping define Huawei's next-generation large-scale data centre and AI infrastructure systems. Positioned at the intersection of advanced systems research and industrial-scale engineering, our team turns innovative system designs into deployable, real-world technologies.
Key Responsibilities
- Distributed Systems Research & Development: Architect, implement, and evaluate distributed system components for emerging AI and data-centric workloads. Drive modular design and scalability across CPU, GPU, and NPU clusters, building highly efficient serving and scheduling systems.
- Performance Optimization & Profiling: Conduct in-depth profiling and performance tuning of large-scale inference and data pipelines, focusing on KV cache management, heterogeneous memory scheduling, and high-throughput inference serving using frameworks like vLLM, Ray Serve, and modern PyTorch distributed systems.
- Scalable Model Serving Infrastructure: Develop and evaluate frameworks that enable efficient multi-tenant, low-latency, and fault-tolerant AI serving across distributed environments. Research and prototype new techniques for cache sharing, data locality, and resource orchestration and scheduling within AI clusters.
- Research & Publications: Translate innovative research ideas into publishable contributions at leading venues (e.g., OSDI, NSDI, EuroSys, SoCC, MLSys, NeurIPS, ICML, ICLR) while driving internal adoption of novel methods and architectures.
- Cross-Team Collaboration: Communicate technical insights, research progress, and evaluation outcomes effectively to multidisciplinary stakeholders and global Huawei research teams.
Required Qualifications and Skills
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
- Strong knowledge of distributed systems, operating systems, machine learning systems architecture, inference serving, and AI infrastructure.
- Hands-on experience with LLM serving frameworks (e.g., vLLM, Ray Serve, TensorRT-LLM, TGI) and distributed KV cache optimization.
- Proficiency in C/C++, with additional experience in Python for research prototyping.
- Solid grounding in systems research methodology, distributed algorithms, and profiling tools.
- Team-oriented mindset with effective technical communication skills.
Desired Qualifications and Experience
- PhD in systems, distributed computing, or large-scale AI infrastructure.
- Publications in top-tier systems or ML conferences (NSDI, OSDI, EuroSys, SoCC, MLSys, NeurIPS, ICML, ICLR).
- Understanding of load balancing, state management, fault tolerance, and resource scheduling in large-scale AI inference clusters.
- Prior experience designing, deploying, and profiling high-performance cloud or AI infrastructure systems.
Systems Research Engineer employer: Huawei Technologies Research & Development (UK) Ltd
Contact Detail:
Huawei Technologies Research & Development (UK) Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Systems Research Engineer
✨Tip Number 1
Network like a pro! Attend industry meetups, conferences, or webinars related to AI and distributed systems. It's all about making connections that could lead to job opportunities, so don’t be shy – introduce yourself and share your passion!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving distributed systems or AI infrastructure. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on technical concepts and common interview questions in your field. Practice explaining your past projects and how they relate to the role you're applying for – confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight your relevant experience and enthusiasm for the role.
We think you need these skills to ace Systems Research Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Systems Research Engineer role. Highlight your knowledge of distributed systems and any hands-on experience with LLM serving frameworks. We want to see how you fit into our vision!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI infrastructure and how your background aligns with our goals at Huawei. Let us know what excites you about the role and the impact you hope to make.
Showcase Your Research Experience: If you've got publications or research projects, don’t hold back! Share them in your application. We love seeing innovative ideas and how you’ve contributed to the field. It’s all about demonstrating your expertise and enthusiasm for systems research.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets to the right people. Plus, it shows us you’re serious about joining our team at the Edinburgh Research Centre!
How to prepare for a job interview at Huawei Technologies Research & Development (UK) Ltd
✨Know Your Distributed Systems
Make sure you brush up on your knowledge of distributed systems and AI infrastructure. Be ready to discuss specific frameworks like vLLM and Ray Serve, and how they relate to the role. Showing that you understand the intricacies of these systems will impress the interviewers.
✨Showcase Your Research Skills
Prepare to talk about any research you've conducted, especially if it relates to large-scale AI or distributed computing. If you have publications, be ready to discuss them in detail. This demonstrates not only your expertise but also your ability to contribute to Huawei's innovative projects.
✨Communicate Effectively
Since the role involves cross-team collaboration, practice explaining complex technical concepts in simple terms. Think about how you would communicate your ideas to non-technical stakeholders. Clear communication can set you apart from other candidates.
✨Hands-On Experience Matters
Be prepared to discuss your hands-on experience with relevant technologies, particularly C/C++ and Python. Share specific examples of projects where you optimised performance or developed scalable systems. This practical knowledge is crucial for the role and will show that you're ready to hit the ground running.
