4 of 4 Permanent vLLM Jobs in Edinburgh

Google Professional Cloud Architect, TOGAF, or equivalent). Experience with large language model training and inference architecture at scale (e.g., PyTorch, DeepSpeed, Megatron-LM, vLLM). Experience with edge and on-device AI inference and the device-to-cloud continuum. Advanced Kubernetes experience: GPU scheduling plugins, multi-cluster and fleet ...

optimise models using cloud services like AWS Bedrock and Azure AI Foundry, or self-host them on GPU/CPU hardware using tools like vLLM, SGLang, and Ollama.Solution Evaluation: Implement frameworks and approaches to evaluate model performance against business objectives, both pre-deployment and on an ongoing basis as part ...

Strong knowledge of distributed systems, operating systems, machine learning systems architecture, Inference serving, and AI Infrastructure. Hands-on experience with LLM serving frameworks (e.g., vLLM, Ray Serve, TensorRT-LLM, TGI) and distributed KV cache optimization. Proficiency in C/C++, with additional experience in Python for research prototyping. Solid grounding ...

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 … 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 ...