AI System Researcher

microTECH Global Limited; City of Edinburgh; Hybrid; GBP 65.000 - 90.000; Vollzeit

Benefits dieser Stelle

Restaurant d'entreprise

Zusammenfassung

microTECH Global Limited is seeking Systems Research Engineers with a strong interest in computer systems, distributed AI infrastructure, and performance optimization. Recent PhD graduates or exceptional BSc/MSc engineers will join a research-driven team building in areas such as operating systems, distributed systems, AI model serving, and ML infrastructure.

You will work closely with senior architects on real-world projects, helping to prototype and optimize next-generation AI infrastructure.

Qualifikationen

• PhD in systems, distributed computing, or related field preferred.
• Bachelor’s or Master’s in CS/EE or related field required.
• Hands-on with LLM serving frameworks and AI infrastructure tooling.

Aufgaben

• Prototype and optimize next-generation AI infrastructure.
• Collaborate with senior architects on real-world projects.
• Advance OS and distributed systems research within production-like environments.

Kenntnisse

Distributed systems

Operating systems

ML infrastructure

Inference serving

C/C++

Python

Research methodology

Distributed algorithms

Profiling tools

Team communication

Ausbildung

PhD in systems / distributed computing / large-scale AI infrastructure

Bachelor’s or Master’s in Computer Science or Electrical Engineering

Tools

vLLM

Ray Serve

TensorRT-LLM

TGI

Distributed KV cache tooling

Jobbeschreibung

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.