Systems Research Engineer - #2158706

Systems Research Engineer | AI Infrastructure | C++ Systems Engineering

One of the largest telecommunications companies in the world is looking for an experienced researcher to join the company in Edinburgh.

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.

Who You Are

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 [email protected]

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