Machine Learning Engineer (AI / LLM Systems)

We’re working with a well-established, tech-led business that is building a new AI product focused on real-world tasks, workflows, and decision-making.

This is a small, high-calibre team building systems where model capability is transformed into reliable, production-grade ML systems, with a strong emphasis on ownership, iteration, and real-world performance.

The product focuses on:

Long-running AI workflows

Persistent context across interactions

Multi-step reasoning and task execution

Integration with external tools and systems

The core challenge is designing ML systems that can behave reliably in production, even when model outputs are inherently non-deterministic.

The Role

This role sits at the core of the ML layer powering the product.

The focus is on designing and operating systems that enable:

ML models to run reliably in production

End-to-end pipelines from training to inference

Continuous evaluation and iterative improvement

Model behaviour debugging and failure analysis

Latency, throughput, and cost optimisation

Monitoring, observability, and evaluation frameworks

Scaling ML systems in production environments

Tech Environment

Python (core ML and backend language)

PyTorch / modern ML frameworks

LLM ecosystem (OpenAI, Anthropic, etc.)

GPU-based training and inference

Docker and Kubernetes

AWS, Azure or GCP

The emphasis is on how you build and operate ML systems, rather than specific tools.

Team & Working Style

Fully remote-first, work from anywhere

Small, highly capable engineering team

Strong emphasis on ownership and delivery

Fast iteration cycles with real user feedback

Comfortable working in evolving systems and making pragmatic decisions, Senior (5+ years of experience)

Tagged as: Industry, Machine Learning, NLP, United Kingdom

Nicoll Curtin