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AI Systems Research Engineer Permanent Edinburgh (On-site 5 days work ) salary : Competitive and negotiable In an era where Large Language Models (LLMs) are rebuilding the foundational software stack, our client is at the forefront of reshaping how large-scale models are trained, served, and deployed. Operating at the intersection of advanced systems research and industrial-scale engineering, their Edinburgh-based team is driving new AI Infrastructure & Agentic Serving architectures. This role is a unique opportunity to help define next-generation large-scale data centres and AI infrastructure systems, turning innovative system designs into deployable, real-world technologies. We are seeking Systems Research Engineers with a deep passion for computer systems, distributed AI infrastructure, and performance optimization. These roles are ideal for recent PhD graduates or exceptional BSc/MSc engineers looking to build research-driven experience in Operating Systems, Distributed Systems, AI Model Serving, Machine learning infrastructure. You will work closely with architects to prototype and optimize the next generation of global AI clusters. What you will be doing • Distributed Systems Research & Development : Architect, implement, and evaluate distributed system components for emerging AI and data-centric workloads. Drive modular design and scalability across 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., OSDI, NSDI, EuroSys, SoCC, MLSys, NeurIPS, ICML, ICLR) while driving internal adoption of novel methods and architectures., • Cross-Team Collaboration : Communicate technical insights, research progress, and evaluation outcomes effectively to multidisciplinary stakeholders and global research teams What we are looking for • Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field / 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., • Hands-on experience with LLM Inference and LLM serving frameworks (e.g., vLLM, Ray Serve, TensorRT-LLM, TGI, PyTorch) and distributed KV cache optimization., • Familiarity with GPU and how they execute LLMs, • Solid grounding in systems research methodology, distributed algorithms, and profiling tools., • Proficiency in C/C++, with additional experience in Python for research prototyping., • Team-oriented mindset with effective technical communication skills If this sounds like a role you can take hold of, we would love to hear from you! To apply for this role, please send your CV to Maggie Kwong Great journeys start here, apply now!

Systems Research Engineer | 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 By applying to this role you understand that we may collect your personal data and store and process it on our systems. For more information please see our Privacy Notice ()

Systems Research Engineer - Distributed Systems / C++ We are currently partnered with a globally leading research centre in the UK looking to expand their team with a Systems Research Engineer. This is an incredibly high calibre team reshaping how large-scale models are trained and served through next-generation AI-native infrastructure and "super-node" clusters. This is a permanent opportunity based onsite in Edinburgh. Key responsibilities for this Systems Research Engineer position: • Architect and implement distributed system components for AI workloads across CPU, GPU, and NPU clusters., • Conduct in-depth profiling and performance tuning of inference pipelines, focusing on KV cache management., • Develop low-latency, fault-tolerant AI serving frameworks using vLLM, Ray Serve, and PyTorch Distributed., • Research and prototype novel techniques for cache sharing, data locality, and resource orchestration., • Translate innovative designs into publishable contributions at top-tier venues (e.g., OSDI, NSDI, MLSys)., • Collaborate with global research teams to drive the internal adoption of novel system architectures. Key Requirements: • Preferably a PhD, at minimum a masters degree, in Computer Science, distributed systems, or related field., • Strong knowledge of Distributed Systems, OS internals, and Machine Learning systems architecture., • Hands-on experience with LLM serving frameworks (vLLM, Ray Serve, TensorRT-LLM, or TGI)., • Proficiency in C/C++ for systems development and Python for research prototyping., • Solid grounding in distributed algorithms, load balancing, and state management., • Proven ability to conduct systems research, ideally evidenced by publications in top-tier conferences. Keywords: Systems Research Engineer / Distributed Systems / AI Infrastructure / LLM Serving / vLLM / KV Cache / Performance Optimization / Machine Learning Systems / C++ / Python / Ray Serve / PyTorch Distributed / Cloud Infrastructure If you are interested in this Systems Research Engineer position, please send a copy of your CV to By applying to this role you understand that we may collect your personal data and store and process it on our systems. For more information please see our Privacy Notice

A dynamic software scale-up seeks a Senior Quality Engineer to lead quality assurance for large language model-powered systems.In this hands-on role, you will improve regression testing strategies, manage test infrastructure, and shape quality approaches throughout the lifecycle.You will collaborate

A leading AI solutions company in Scotland seeks an Applied AI Solution Engineer to build and deploy AI applications.This role involves hands-on solution design and development, extensive client interaction, and problem-solving in AI development.Candidates should have experience with microservices,

A leading global professional services company in the UK seeks a highly skilled AI LLM Technology Architecture Associate Manager to design and implement AI/ML technology solutions.

AI LLM Technology Architecture Associate Manager. AI LLM Architecture Associate Manager.

Full Stack LLM Development Manager. As a Full Stack LLM Development Manager, you will.

A leading professional services firm is seeking a Consultant – Applied AI Engineer to develop AI-powered solutions for financial services clients.This hybrid role requires proficiency in software development, basic AI concepts, and cloud services, particularly Azure.The ideal candidate will engage

A leading AI-focused technology firm in the City of Edinburgh seeks a candidate with experience in large language models and prompt engineering.The role involves crafting AI prompts, collaborating with various teams for regulatory compliance, and shaping AI technical requirements.Ideal candidates wi

Full Stack LLM Development Manager.

LLMs, intelligent agents, and automation drive core capabilities—not just features. LLMs (using SFT/RLHF) as production-ready systems, including:.

LLM-driven discovery and generative interfaces. LLM search, generative interfaces, and emerging agent-based ecosystems. AI search, LLM visibility, and evolving acquisition strategies.

You are proficient in Python/PyTorch and comfortable with the modern LLM stack (vLLM, HuggingFace, fine-tuning pipelines, eval frameworks). LLM team (currently 3 engineers) and own the architecture, training, and deployment of the models that power our core product. You have 8+ years of engineering

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English LLM Data Annotator/Evaluator.

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A global professional services company is seeking a Full Stack LLM Development Manager in Edinburgh.

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Integrate and fine-tune commercially available LLMs (e. Implement multi-step LLM workflows using orchestration frameworks like LangChain. Proven experience working within complex, unified codebases that combine application logic with AI/LLM components.

A cybersecurity firm in the United Kingdom is seeking a Cybersecurity Specialist on a contract basis to evaluate and secure large language models (LLMs). Candidates should have an interest in cybersecurity, proficiency in LLM usage, and completed a Red Team Academy certification.

A leading technology investor is seeking a Senior AI Engineer to drive the development of LLM-powered products in marketing and advertising.

Continuously track developments in LLMs, agent frameworks, and broader AI trends relevant to enterprise and security use cases. AI/ML, with 3+ years focused on LLMs, generative models, or agent-based systems.

This range is provided by YO IT Group.Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.Anywhere in the World - Permanent Remote.Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience).At least 4 years of relevan

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Key responsibilities include designing and maintaining SDKs, deploying AI workloads in cloud environments, and refining LLM orchestration strategies.

This fully remote role involves architecting LLMOps pipelines, developing machine learning models, and collaborating with cross-functional teams.

A leading AI consulting firm in the United Kingdom is currently seeking to fill an entry-level position focused on designing evaluation scenarios for LLM-based agents.

A forward-thinking AI company in the United Kingdom is seeking a Gen-AI Prompt & Context Engineer to design and operate LLM workflows.

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A leading AI companionship company in the UK is seeking a Tech Lead to manage an LLM team focused on creating advanced AI companion systems.

The successful candidate will collaborate with cross-functional teams to design and implement effective LLM solutions.

Fine-tuning LLMs on custom datasets to enhance performance for specialized tasks related to our documentation and user support. Proven experience building and deploying applications with LLM APIs such as. Practical knowledge of LLM fine-tuning, prompt engineering, and performance optimization.

Senior LLM, RAG & Agentic AI Consulting Engineer - Lead / Senior FDE. LLM applications using modern orchestration patterns, prompt frameworks and evaluation loops. Strong hands-on experience with LLMs, embeddings, RAG, retrieval stacks and vector databases.

LLM Engineer – Retrieval & Knowledge Systems. We’re looking for an LLM Engineer to design and deploy retrieval-augmented generation (RAG) systems powering intelligent applications used in enterprise and research environments. This role goes beyond prompt engineering — you’ll work on end-to-e

LLMs (using SFT/RLHF) as production-ready systems, including:. LLMs, intelligent agents, and automation drive core capabilities—not just features.

Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM.

You will play a central role in shaping how modern AI technologies (LLMs, prompt engineering, ML models) are embedded into both the product and the broader business. LLMs and prompt engineering techniques.

Leading the design of multi-agent systems and LLM orchestration patterns. LangGraph · Pydantic AI · Agent SDK · LLMOps. Shaping the infrastructure behind model serving, training pipelines, LLMOps, and AgentOps across the full AI stack.

Build and optimise LLM-powered audio pipelines and extend our Qwen-based vision model for audio production use cases.

Building and optimising machine learning and LLM-based models. Experience with LLMs, NLP, or deep learning models. Alongside this, they are developing private, enterprise-grade language models, allowing organisations to securely deploy LLM-powered analytics within their own environments; this is a h

A fast-growing technology business focused on sustainable operations for large, multi-site organisations.The platform brings together building, asset and energy data into one place, giving customers full visibility and control across their estate.The product uses connected device data, automation an

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