Senior Machine Learning Engineer (AI/LLM Systems)

Salary: £68,000 - 108,000 per year

Requirements:

• Experience shipping machine learning systems used by real users
• Experience owning machine learning systems end-to-end in production
• Experience working with modern LLMs beyond simple API integration
• Practical experience debugging model behaviour and analysing failures
• Experience optimising latency, throughput, and cost
• Familiarity with monitoring, observability, and evaluation frameworks
• Experience scaling machine learning systems in production environments
• Familiarity with Python, PyTorch or modern machine learning frameworks, LLM platforms, GPU-based training and inference, Docker, Kubernetes, and AWS, Azure, or GCP

Responsibilities:

• Design and operate systems that enable machine learning models to run reliably in production
• Build and maintain end-to-end pipelines from training through inference
• Support continuous evaluation and iterative improvement of machine learning systems
• Develop training, inference, and evaluation pipelines for LLM-based systems and agent-style workflows
• Debug model behaviour using real-world signals
• Optimise system performance across latency, cost, and reliability
• Maintain production monitoring, logging, and system stability

Technologies:

• AI
• API
• AWS
• Azure
• Docker
• Support
• Kubernetes
• LLM
• Machine Learning
• PyTorch
• Python
• Cloud
• Backend
• GCP

More:

We are working with a well-established, technology-led business building a new AI product focused on real-world tasks, workflows, and decision-making. Our product supports long-running AI workflows, persistent context across interactions, multi-step reasoning and task execution, and integration with external tools and systems. This role is at the core of the machine learning layer powering the product, where we turn model capabilities into reliable, production-grade systems. We are a small, high-calibre engineering team with a strong emphasis on ownership, delivery, fast iteration, and real user feedback. We are fully remote-first, with the role based anywhere in the United Kingdom, and offer permanent employment with flexible compensation and equity. We value pragmatic decision-making and comfort working in evolving systems; our emphasis is on how systems are built and operated rather than on specific tools.

last updated 40 week of 2026