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- Tasks: Join us to optimise next-gen AI infrastructure and work on real-world projects.
- Company: Leading tech firm focused on cutting-edge AI and systems research.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Make a tangible impact in the exciting field of AI and distributed systems.
- Qualifications: Degree in Computer Science or related field; strong knowledge of distributed systems required.
- Other info: Collaborative environment with mentorship from senior architects and excellent 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:
- 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.
esearch (Systems) Engineer in Dalkeith 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 Dalkeith
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage in online forums. We all know that sometimes it’s not just what you know, but who you know that can land you that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects related to distributed systems and 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 those interviews! Brush up on your technical knowledge and be ready to discuss your experience with LLM serving frameworks and distributed algorithms. We recommend practicing common interview questions and even doing mock interviews with friends.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace esearch (Systems) Engineer in Dalkeith
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 systems engineering and how your background makes you a perfect fit for our team. Keep it engaging and personal!
Showcase Your Technical Skills: Don’t forget to mention your hands-on experience with LLM serving frameworks and programming languages like C/C++ and Python. We love seeing practical examples of your work, so include any relevant projects or publications!
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, operating systems, and AI infrastructure. Be ready to discuss specific frameworks like vLLM or Ray Serve, and don’t shy away from diving into technical details. This shows you’re not just familiar with the concepts but can also apply them.
✨Showcase Your Projects
Prepare to talk about any relevant projects you've worked on, especially those involving machine learning systems or cloud infrastructure. Highlight your hands-on experience with LLM serving frameworks and how you tackled challenges in those projects. Real-world examples will make you stand out!
✨Communicate Clearly
Since this role requires effective technical communication, practice explaining complex ideas in simple terms. You might be asked to explain your research methodology or a distributed algorithm, so clarity is key. Think about how you would explain these concepts to someone without a technical background.
✨Ask Insightful Questions
Prepare some thoughtful questions about the company’s current projects or future directions in AI infrastructure. This not only shows your interest but also gives you a chance to demonstrate your understanding of the field. It’s a great way to engage with your interviewers and leave a lasting impression.
