Machine Learning Engineer (Remote)

Understanding Recruitment; United Kingdom; Hybrid; GBP 70,000 - 120,000; Full time

Benefits offered by this job

Remote work flexibility

Job summary

Understanding Recruitment is seeking an ML Engineer to build, deploy and scale production AI systems. You will work across ML Engineering, Software Engineering and Cloud Infrastructure, owning the end-to-end lifecycle from Python development to AWS deployment.

Ideal candidates bring strong Python and AWS experience, plus hands-on exposure to containers and CI/CD. Remote-friendly role with optional office access, offering growth toward senior leadership opportunities.

Qualifications

• Strong Python engineering skills with production experience.
• Hands-on AWS, CI/CD, containers and cloud infrastructure experience.
• Experience deploying, monitoring and maintaining production ML/AI systems.
• Exposure to LLMs, RAG or GenAI applications.

Responsibilities

• Build and scale production AI/LLM systems, including RAG and agentic workflows.
• Own the full engineering lifecycle from Python development through to AWS deployment.
• Work with Python, FastAPI, AWS, Docker, CI/CD and infrastructure-as-code.
• Solve reliability, observability, performance and cost challenges.
• Influence technical decisions and grow toward Senior/Lead ownership.

Skills

Python

AWS

CI/CD

Docker

FastAPI

Tools

Docker

AWS

CI/CD

FastAPI

Job description

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

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

Why it's interesting:

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

What we're looking for:

• Strong Python engineering skills and experience building production services
• Hands-on AWS, CI/CD, containers and cloud infrastructure experience
• Experience deploying, monitoring and maintaining production ML/AI systems
• Exposure to LLMs, RAG or GenAI applications
• An engineer who enjoys debugging complex systems and taking end-to-end ownership

Ideally 4+ years' experience, but technical depth and production engineering experience matter more than tenure.

This could suit someone coming from ML Engineering, MLOps, Platform Engineering or backend Software Engineering who wants to work closer to production AI.