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For Companies At a Glance
- Tasks: Join us to optimise next-gen AI infrastructure and work on real-world projects.
- Company: Leading tech firm focused on cutting-edge systems research and AI.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Make a significant impact in the AI field while collaborating with top experts.
- Qualifications: BSc/MSc in Computer Science or related field; PhD preferred.
- Other info: Dynamic team environment with a focus on innovation and research.
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:
- Bachelors or Masters 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.
Locations
esearch (Systems) Engineer in Edinburgh, Scotland employer: Microtech Global Ltd
Contact Detail:
Microtech Global Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land esearch (Systems) Engineer in Edinburgh, Scotland
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage in online forums. The more people you know, the better your chances of landing that Systems Research Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to distributed systems and AI infrastructure. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common interview questions related to operating systems and machine learning systems architecture to impress your future team.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for passionate engineers like you. Keep an eye on our job postings and make sure your application stands out!
We think you need these skills to ace esearch (Systems) Engineer in Edinburgh, Scotland
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in computer systems and distributed AI infrastructure. We want to see how your skills align with the role, so don’t be shy about showcasing your projects and any hands-on experience you've had!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about systems research and how your background makes you a great fit for our team. We love seeing enthusiasm and a clear connection to the role.
Showcase Your Technical Skills: Be sure to mention your proficiency in C/C++ and Python, as well as any experience with LLM serving frameworks. We’re looking for candidates who can hit the ground running, so highlight any relevant projects or research that demonstrate your technical prowess.
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 shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Microtech Global Ltd
✨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 your 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 performance optimisation. 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 clear and concise is key. Think of it as telling a story that anyone can understand.
✨Ask Smart Questions
At the end of the interview, don’t forget to ask insightful questions about the team’s current projects or future directions in AI infrastructure. This shows your genuine interest in the role and helps you gauge if the company is the right fit for you.
