Systems Research Engineer

A global telecommunications and technology leader is hiring contract System Research Engineers to join an advanced Research & Development lab in Edinburgh.

Positioned at the intersection of advanced research and practical engineering, this team translates cutting-edge innovations into real-world data centre solutions. These contract roles are ideal for recent PhD graduates seeking industrial research experience, or exceptional BSc/MSc graduates looking to deepen their research capabilities in an industry setting.

• Rapid Prototyping: Collaborate with a multidisciplinary team to rapidly build and evaluate proof-of-concept prototypes, validating research ideas in real-world environments.
• Performance Optimization: Perform detailed profiling and optimization of operating systems and large-scale distributed systems across heterogeneous hardware platforms (e.g., CPU, NPU).
• Research Publications: Turn research findings and innovative contributions into high-impact publications for top-tier academic journals and conferences.
• Technical Documentation: Maintain comprehensive technical documentation detailing research methods, design decisions, and implementation specifics to ensure reproducibility and internal knowledge sharing.
• Stakeholder Engagement: Present research progress, performance insights, and technical outcomes to internal stakeholders.

• Education: Bachelor's or Master's degree in Computer Science or a related technical discipline.
• Research
  
  Skills:
  
  Comfortable with research methodologies and experimental design.
• Technical Expertise: In-depth understanding of operating systems, distributed systems, cloud computing, or machine learning systems.
• Programming: Strong coding proficiency in at least one key language (such as C or C++).
• Soft Skills: Excellent communication and collaborative teamwork abilities.
• PhD in operating systems, distributed systems, or machine learning systems.
• Track record of publications in top systems (e.g., NSDI, Euro Sys, SoCC, OSDI) or machine learning (e.g., NeurIPS, ICML, ICLR) conferences and journals.
• Hands-on experience in the full lifecycle of developing, deploying, and maintaining large-scale cloud production systems, focusing on scalability, reliability, and performance.

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