Research Systems Engineer

Systems Research Engineer European Tech Recruit are working closely with a leading telecommunications & research company, based in Edinburgh, who are looking for a talented Systems Research Engineer to join their team . In this role you will join a research centre driving new AI Infra & Agentic Serving architectures and helping define the next-generation large-scale data centre and AI infrastructure systems. Positioned at the intersection of advanced systems research and industrial-scale engineering, our client's teams turn innovative system designs into deployable, real-world technologies. This role is ideal for recent PhD graduates 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. Responsibilities as Systems Research Engineer: Distributed Systems Research & Development: Architect, implement, and evaluate distributed system components for emerging AI and data-centric workloads. Drive modular design and scalability across CPU, GPU, and NPU clusters, building highly efficient serving and scheduling systems. Performance Optimization & Profiling: Conduct in-depth profiling and performance tuning of large-scale inference and data pipelines, focusing on KV cache management, heterogeneous memory scheduling, and high-throughput inference serving using frameworks like vLLM, Ray Serve, and modern PyTorch Distributed systems. Scalable Model Serving Infrastructure: Develop and evaluate frameworks that enable efficient multi-tenant, low-latency, and fault-tolerant AI serving across distributed environments. Research and prototype new techniques for cache sharing, data locality, and resource orchestration and scheduling within AI clusters. Research & Publications: Translate innovative research ideas into publishable contributions at leading venues (e.g., Cross-Team Collaboration: Communicate technical insights, research progress, and evaluation outcomes effectively to multidisciplinary stakeholders and global research teams. PhD in systems, distributed computing, or large-scale AI infrastructure. Strong knowledge of distributed systems, operating systems, machine learning systems architecture, Inference serving, and AI Infrastructure. Proficiency in C/C++, with additional experience in Python for research prototyping. Solid grounding in systems research methodology, distributed algorithms, and profiling tools. 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. By applying to this role you understand that we may collect your personal data and store and process it on our systems.