Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join us to optimise and prototype next-gen AI infrastructure in a collaborative environment.
- Company: Leading tech firm in Edinburgh focused on cutting-edge AI research.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Be at the forefront of AI technology and make a real impact in the field.
- Qualifications: Degree in Computer Science or related field; strong knowledge of distributed systems required.
- Other info: Ideal for recent graduates eager to dive into innovative projects with industry experts.
The predicted salary is between 36000 - 60000 £ per year.
We are seeking Systems Research Engineers with a strong interest in computer systems, distributed AI infrastructure, and performance optimization. These roles are ideal for recent PhD graduates or exceptional BSc/MSc engineers 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.
Required Qualifications and Skills
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or 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.
AI Research (Systems) Engineer - Edinburgh employer: microTECH Global Limited
Contact Detail:
microTECH Global Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Research (Systems) Engineer - Edinburgh
✨Tip Number 1
Network like a pro! Attend industry meetups, conferences, or online webinars related to AI and systems engineering. Engaging with professionals in the field can open doors and lead to job opportunities that aren't even advertised.
✨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 tangible sense of what you can do and sets you apart from the crowd.
✨Tip Number 3
Don’t just apply; engage! When you find a role that excites you, reach out to current employees on LinkedIn. Ask them about their experiences and express your enthusiasm for the position. It’s a great way to make a memorable impression.
✨Tip Number 4
Keep it real! Prepare for interviews by practising common technical questions related to distributed systems and AI infrastructure. We recommend doing mock interviews with friends or using platforms that simulate real interview scenarios.
We think you need these skills to ace AI Research (Systems) Engineer - Edinburgh
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with distributed systems and AI infrastructure. We want to see how your skills match the role, so don’t be shy about showcasing relevant projects or research!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI and systems engineering. We love seeing enthusiasm, so let us know what excites you about this field and why you want to join our team.
Showcase Your Technical Skills: Be specific about your hands-on experience with tools like vLLM or TensorRT-LLM. We’re looking for candidates who can hit the ground running, so highlight any relevant projects or achievements that demonstrate your expertise.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts and you’ll be all set!
How to prepare for a job interview at microTECH Global Limited
✨Know Your Stuff
Make sure you brush up on your knowledge of distributed systems and AI infrastructure. Be ready to discuss specific frameworks like vLLM or Ray Serve, and how you've used them in past projects. This shows you're not just familiar with the theory but have practical experience too.
✨Showcase Your Projects
Prepare to talk about any relevant projects you've worked on, especially those involving machine learning systems or high-performance cloud infrastructure. Highlight your role, the challenges you faced, and how you overcame them. Real-world examples can really make you stand out!
✨Communicate Clearly
Since this role requires effective technical communication, practice explaining complex concepts in simple terms. You might be asked to explain your research methodology or a distributed algorithm, so being able to articulate your thoughts clearly is key.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the team’s current projects or the company’s approach to optimising AI infrastructure. This shows your genuine interest in the role and helps you gauge if it’s the right fit for you.
