At a Glance
- Tasks: Join a team driving AI infrastructure research and develop cutting-edge distributed systems.
- Company: Leading telecommunications and research company based in Edinburgh.
- Benefits: Competitive salary, opportunities for research publications, and collaboration with senior architects.
- Other info: Dynamic research environment with opportunities for career growth and innovation.
- Why this job: Make an impact in AI and data-centric workloads while advancing your engineering career.
- Qualifications: PhD in systems or distributed computing, strong knowledge of AI infrastructure, and proficiency in C/C++.
The predicted salary is between 50000 - 70000 £ per year.
European Tech Recruit are working closely with a leading telecommunications & research company, based in Edinburgh, who are looking for a talented Systems Research Engineer to join their team. In this role you will join a research centre driving new AI Infra & Agentic Serving architectures and helping define the next-generation large-scale data centre and AI infrastructure systems. Positioned at the intersection of advanced systems research and industrial-scale engineering, our client's teams turn innovative system designs into deployable, real-world technologies. This role is ideal for recent PhD graduates looking to build research-driven engineering experience in areas such as operating systems, distributed systems, AI model serving, and machine learning infrastructure. You will work closely with senior architects on real-world projects, helping to prototype and optimize next-generation AI infrastructure.
Responsibilities as Systems Research Engineer:
- 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.
- Cross-Team Collaboration: Communicate technical insights, research progress, and evaluation outcomes effectively to multidisciplinary stakeholders and global research teams.
Qualifications:
- PhD in systems, distributed computing, or large-scale AI infrastructure.
- Strong knowledge of distributed systems, operating systems, machine learning systems architecture, inference serving, and AI infrastructure.
- Proficiency in C/C++, with additional experience in Python for research prototyping.
- Solid grounding in systems research methodology, distributed algorithms, and profiling tools.
- 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 Engineering Scientist in Edinburgh employer: European Tech Recruit
Join a pioneering telecommunications and research company in Edinburgh, where innovation meets real-world application. As a Systems Research Engineer, you'll thrive in a collaborative environment that fosters professional growth and encourages cutting-edge research in AI infrastructure. With access to advanced technologies and the opportunity to work alongside industry experts, this role offers a unique chance to contribute to transformative projects while developing your skills in a supportive and dynamic workplace.
StudySmarter Expert Advice🤫
We think this is how you could land Systems Engineering Scientist in Edinburgh
✨Tip Number 1
Network like a pro! Reach out to professionals in the field of systems engineering and AI infrastructure. Attend meetups, webinars, or conferences where you can connect with industry experts and potential employers. Remember, sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to distributed systems or AI infrastructure. Whether it's a GitHub repository or a personal website, having tangible evidence of your work can really set you apart from other candidates.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your research and projects in detail. Practice common interview questions related to systems engineering and think about how your experience aligns with the role of a Systems Research Engineer.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might be perfect for you. Plus, applying directly can sometimes give you an edge, as we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Systems Engineering Scientist in Edinburgh
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Systems Research Engineer role. Highlight your experience with distributed systems, AI infrastructure, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about this role and how your PhD research relates to our work. We love seeing enthusiasm and a clear connection to the job description.
Showcase Your Publications:If you have publications in top-tier conferences, make sure to mention them! This shows us that you’re not just knowledgeable but also actively contributing to the field. It’s a great way to stand out from the crowd.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Don’t miss out on this opportunity!
How to prepare for a job interview at European Tech Recruit
✨Know Your Systems Inside Out
Make sure you brush up on your knowledge of distributed systems and AI infrastructure. Be ready to discuss specific projects you've worked on, especially those involving performance optimisation and profiling. This will show that you not only understand the theory but can also apply it in real-world scenarios.
✨Showcase Your Research Skills
Since this role involves translating research into practical applications, be prepared to talk about your PhD work and any publications. Highlight how your research can contribute to the company's goals, especially in areas like cache management and resource orchestration.
✨Demonstrate Technical Communication
You'll need to communicate complex ideas to multidisciplinary teams, so practice explaining your technical insights clearly and concisely. Use examples from your past experiences where you successfully collaborated with others to solve problems or drive projects forward.
✨Prepare for Problem-Solving Questions
Expect to face some technical challenges during the interview. Brush up on your problem-solving skills related to load balancing and fault tolerance in AI inference clusters. Practising coding problems in C/C++ and Python can help you feel more confident when tackling these questions.
