Machine Learning Engineer (Remote)

Understanding Recruitment Ltd; United Kingdom; Hybrid; GBP 70,000 - 110,000; Full time

Job summary

Understanding Recruitment Ltd is seeking a Machine Learning Engineer focused on Production AI and LLM systems. You will build, deploy and scale production-grade AI services while owning the end-to-end lifecycle from Python development to AWS deployment.

You will work across ML engineering, backend software engineering and cloud infrastructure to deliver reliable, observable, and cost-efficient systems. This role offers hybrid flexibility and opportunities to influence technical decisions and

Qualifications

• 4+ years in production ML/AI or related engineering.
• Strong Python engineering skills with production services experience.
• Experience deploying, monitoring and maintaining production ML/AI systems.
• Exposure to LLMs, RAG or GenAI applications.

Responsibilities

• Build, deploy and scale production AI/LLM systems.
• Own the full engineering lifecycle from development through to deployment on AWS.
• Collaborate across ML Engineering, Software Engineering and Cloud Infrastructure to deliver reliable services.
• Drive reliability, observability, performance and cost efficiency across systems.

Skills

Python engineering

AWS

CI/CD

FastAPI

Cloud infrastructure

Production ML/AI systems

LLMs/GenAI

End-to-end ownership

Tools

Docker

Kubernetes

Job description

Machine Learning Engineer | Production AI & LLM Systems

If you're an ML Engineer who enjoysbuilding, deploying and scaling AI systems in production, rather than just experimenting with models, this could be a great fit.

You'll work acrossML Engineering, Software Engineering and Cloud Infrastructure, with real ownership over how AI services are built, deployed and operated.

Why it's interesting:

• Build and scaleproduction AI/LLM systems, including RAG and agentic workflows
• Own the full engineering lifecycle, from Python development through to AWS deployment
• Work withPython, FastAPI, AWS, Docker, CI/CD and infrastructure-as-code
• Solve real engineering challenges aroundreliability, observability, performance and cost
• Influence technical decisions, improve engineering practices and grow towardsSenior/Lead ownership
• Remote flexibility with optional office access

What we're looking for:

• StrongPython engineeringskills and experience building production services
• Hands-onAWS, CI/CD, containers and cloud infrastructureexperience
• Experience deploying, monitoring and maintainingproduction ML/AI systems
• Exposure toLLMs, RAG or GenAI applications
• An engineer who enjoys debugging complex systems and taking end-to-end ownership

Ideally4+ years' experience, but technical depth and production engineering experience matter more than tenure.

This could suit someone coming fromML Engineering, MLOps, Platform Engineering or backend Software Engineeringwho wants to work closer to production AI.