The Vision
We are currently scaling a world-class research team in Edinburgh to redefine the foundational software stack for the LLM era. As AI transitions from experimental to "agentic" and "AI-native" infrastructure, we are building the super-node clusters and distributed architectures that will power the next generation of global data centres.
This is a unique hybrid role positioned at the intersection of academic-grade systems research and industrial-scale engineering. You won’t just be writing papers; you’ll be prototyping and deploying the frameworks that manage GPU/NPU clusters at a massive scale.
The Technical Challenge
As a Systems Research Engineer, you will tackle the "bottleneck" problems of modern AI:
- Distributed Systems R&D: Architecting components for CPU, GPU, and NPU clusters with a focus on modularity and extreme scalability.
- Performance Engineering: In-depth profiling of large-scale inference pipelines, specifically focusing on KV cache management and heterogeneous memory scheduling.
- AI Serving: Optimising high-throughput frameworks (vLLM, Ray Serve, PyTorch Distributed) to ensure low-latency, multi-tenant performance.
- Research Leadership: Contributing to top-tier venues (OSDI, NSDI, EuroSys, MLSys) and driving those innovations into real-world production.
We are looking for "systems-first" thinkers—engineers who understand what happens under the hood of a cluster.
Required Experience:
- Education: A Bachelor’s or Master’s in CS, EE, or a related field (PhD highly preferred).
- The Stack: Strong proficiency in C/C++ for systems work, with Python for rapid prototyping.
- Expertise: Hands-on experience with LLM serving frameworks (vLLM, Ray Serve, TensorRT-LLM) and distributed algorithms.
- Mindset: A solid grounding in systems research methodology and performance profiling tools.
The "Value Add" (Desired):
- A PhD focused on distributed computing or AI infrastructure.
- A track record of publications at major conferences (NeurIPS, ICML, ICLR, etc.).
- Deep knowledge of load balancing, fault tolerance, and resource orchestration in massive AI clusters.
Why Join This Team?
- Impact: Work on one of the largest R&D footprints globally.
- Collaboration: Partner with senior architects and global research teams to solve problems that don\'t have "off-the-shelf" solutions yet.
- Location: Based in the heart of Edinburgh’s thriving tech ecosystem.
Interested? Apply directly through LinkedIn, or send your CV to george@eu-recruit.com
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