At a Glance
- Tasks: Join us to innovate AI systems and optimise cutting-edge infrastructure.
- Company: Leading tech firm focused on AI and distributed systems.
- Benefits: Competitive salary, flexible hours, and opportunities for research-driven growth.
- Other info: Collaborative environment with mentorship from industry experts.
- Why this job: Make a real impact in the future of AI technology.
- Qualifications: PhD or exceptional BSc/MSc in Computer Science or related field.
The predicted salary is between 60000 - 80000 £ 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 employer: microTECH Global LTD
As an AI Systems Research Engineer, you will join a dynamic and innovative team dedicated to pushing the boundaries of AI infrastructure. Our company fosters a collaborative work culture that values continuous learning and professional growth, offering ample opportunities for mentorship and hands-on experience with cutting-edge technologies. Located in a vibrant tech hub, we provide a stimulating environment where your contributions will directly impact the future of AI systems.
StudySmarter Expert Advice🤫
We think this is how you could land AI Systems Research Engineer
✨Tip Number 1
Network like a pro! Reach out to professionals in the AI and systems research fields on LinkedIn or at conferences. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to distributed systems and AI infrastructure. This gives us a tangible sense of what you can do.
✨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.
✨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 take that extra step.
We think you need these skills to ace AI Systems Research Engineer
Some tips for your application 🫡
Show Your Passion:Let us see your enthusiasm for AI systems and research! In your application, highlight any projects or experiences that showcase your interest in distributed systems and performance optimisation. We love candidates who are genuinely excited about the field.
Tailor Your CV:Make sure your CV is tailored to the role. Focus on relevant skills like your experience with LLM serving frameworks and proficiency in C/C++. We want to see how your background aligns with what we're looking for, so don’t hold back!
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you’re the perfect fit. Share your journey in computer science, any publications you have, and how your skills can contribute to our team. Keep it engaging and personal!
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 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 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 it’s the right fit for you.
