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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: Be at the forefront of AI technology and make a significant impact.
- Qualifications: Degree in Computer Science or related field; strong knowledge of distributed systems.
- Other info: Collaborative environment with mentorship from 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 Systems Research Engineer in Broughton 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 Broughton
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and systems research fields. Attend meetups, webinars, or conferences where you can chat with industry experts and potential employers. Remember, sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to distributed systems and AI infrastructure. Whether it's a GitHub repo or a personal website, having tangible evidence of your work can really set you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Brush up on your knowledge of operating systems and distributed algorithms. Be ready to discuss your hands-on experience with LLM serving frameworks and how you've tackled performance optimisation in past projects.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might be perfect for you. Plus, applying directly shows your enthusiasm and commitment to joining our team at StudySmarter.
We think you need these skills to ace AI Systems Research Engineer in Broughton
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 align with 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 systems and how your background makes you a perfect fit for our team. Let us know what excites you about the role!
Showcase Your Technical Skills: Don’t forget to mention your hands-on experience with LLM serving frameworks and your proficiency in C/C++. We love seeing practical examples of your work, so include any relevant projects or publications 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!
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 architecture or performance optimisation. Highlight any hands-on experience you have with C/C++ and Python, and be ready to explain your thought process and the outcomes of your work.
✨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 demonstrates your genuine interest in the role and helps you assess if it's the right fit for you.
✨Communicate Clearly
Since this role requires effective technical communication, practice explaining complex concepts in simple terms. Whether it’s discussing load balancing or fault tolerance, being able to articulate your ideas clearly will impress your interviewers and show that you can work well in a team.