AI Research (Systems) Engineer

microTECH Global Limited; City of Edinburgh; On-site; GBP 80,000 - GBP 100,000; Full time

Job summary

A leading technology firm in the UK is seeking Systems Research Engineers to work on next-generation AI infrastructure. This role is ideal for recent PhD graduates or exceptional BSc/MSc engineers with a strong focus on distributed systems and performance optimization. You will collaborate with senior architects, prototyping, and optimizing AI infrastructures, while utilizing your knowledge in systems research and proficiency in programming languages such as C/C++ and Python.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field.
• Strong knowledge of distributed systems and operating systems.
• Hands-on experience with LLM serving frameworks.
• Proficiency in C/C++ and Python for research prototyping.

Responsibilities

• Work closely with senior architects on real-world projects.
• Help prototype and optimize AI infrastructure.

Skills

Distributed systems

Operating systems

Machine learning systems architecture

C/C++

Python

Technical communication

Education

Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field

Tools

vLLM

Ray Serve

TensorRT-LLM

TGI

Job description

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 inComputer 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 withLLM serving frameworks(e.g.,vLLM,Ray Serve,TensorRT-LLM,TGI) anddistributed KV cache optimization.
• Proficiency inC/C++, with additional experience inPythonfor research prototyping.
• Solid grounding insystems research methodology,distributed algorithms, andprofiling tools.
• Team-oriented mindset with effective technical communication skills.

Desired Qualifications and Experience:

• PhDin systems, distributed computing, or large-scale AI infrastructure.
• Publications intop-tier systems or ML conferences(NSDI, OSDI, EuroSys, SoCC, MLSys, NeurIPS, ICML, ICLR).
• Understanding ofload balancing,state management,fault tolerance, andresource schedulingin large-scale AI inference clusters.
• Prior experience designing, deploying, and profilinghigh-performance cloud or AI infrastructure systems.