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- Tasks: Join us to research and optimise cutting-edge AI systems and infrastructure.
- Company: Leading tech firm focused on innovative AI solutions.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Make a real impact in the AI field while collaborating with top experts.
- Qualifications: Degree in Computer Science or related field; strong knowledge of distributed systems required.
- Other info: Exciting projects 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 Livingston 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 Livingston
✨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. Practice explaining complex concepts in simple terms, as effective communication is key. We want to see how you think and solve problems on the spot!
✨Tip Number 4
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. Don’t hesitate – hit that apply button and let’s get you started on your journey!
We think you need these skills to ace AI Systems Research Engineer in Livingston
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 AI systems and how your background makes you a great fit for our team. Let us know what excites you about the role!
Showcase Your Technical Skills: Be specific about your hands-on experience with tools like vLLM or TensorRT-LLM. We love seeing practical examples of your work, so include any projects or papers that demonstrate your expertise in these areas.
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!
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 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. Whether it's discussing load balancing or fault tolerance, being able to articulate your thoughts clearly will impress your interviewers and show that you can work well in a team.