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- Tasks: Join us to innovate AI systems and optimise performance in real-world projects.
- Company: Leading tech firm focused on cutting-edge AI infrastructure.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make a significant impact in the AI field while collaborating with top experts.
- Qualifications: Degree in Computer Science or related field; strong knowledge of distributed systems.
- Other info: Exciting environment with potential for groundbreaking research and career advancement.
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 Systems Research Engineer in Edinburgh employer: Microtech Global Ltd
Contact Detail:
Microtech Global Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Systems Research Engineer in Edinburgh
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with alumni from your university. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to distributed systems and AI infrastructure. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of C/C++ and Python. Practice coding challenges and be ready to discuss your experience with LLM serving frameworks and distributed algorithms. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for passionate individuals like you. Tailor your application to highlight your relevant experience and show us why you’d be a great fit for our team.
We think you need these skills to ace AI Systems Research Engineer in 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 job description, 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 systems and how your background makes you a great fit for our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Technical Skills: When listing your technical skills, be specific! Mention your hands-on experience with LLM serving frameworks and any relevant programming languages like C/C++ and Python. We’re keen to know what tools you’ve used and how you’ve applied them.
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. Plus, it shows us you’re serious about joining the StudySmarter team!
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 your past projects, especially those related to machine learning systems or performance optimisation. Highlight any publications or presentations you've done at conferences. This will demonstrate your commitment to the field and your ability to contribute to real-world applications.
✨Ask Smart Questions
Interviews are a two-way street! Prepare insightful questions about the company's current projects or challenges they face in AI infrastructure. This not only shows your interest but also your understanding of the industry and the role you’re applying for.
✨Communicate Clearly
Since this role requires effective technical communication, practice explaining complex concepts in simple terms. Use examples from your experience to illustrate your points. This will help you connect with the interviewers and show that you can work well in a team-oriented environment.