AI & Emerging technologies

Machine Learning Engineer

Understanding Recruitment

United Kingdom · Nationwide · United Kingdom

Machine Learning Engineer – Python & Production AI

We're working with an exciting technology company looking to hire a Machine Learning Engineer with a strong Python software engineering background to help build, deploy, and scale production-grade AI and machine learning systems.

This isn't a traditional Data Science or research-focused position. We're looking for someone who enjoys taking machine learning models beyond experimentation and turning them into reliable, scalable, real-world applications.

The ideal candidate will combine hands-on machine learning experience with strong software engineering fundamentals, particularly across Python development, backend systems, APIs, testing, deployment, and production infrastructure.

What We're Looking For

  • Strong commercial experience developing production software usingPython .
  • Experience working as a Machine Learning Engineer, Software Engineer, AI Engineer, or in a similar engineering-focused role.
  • Solid understanding of software engineering principles, including object-oriented programming, system design, testing, and maintainable code.
  • Hands-on experience building APIs and backend services using technologies such asFastAPI, Flask, or Django .
  • Experience deploying, maintaining, and monitoring machine learning models in production.
  • Familiarity with ML frameworks such asPyTorch, TensorFlow, or scikit-learn .
  • Experience with cloud platforms such as AWS, GCP, or Azure.
  • Understanding of containerisation, CI/CD pipelines, and modern deployment practices.
  • A genuine engineering mindset, with a focus on building robust, scalable, and maintainable systems.

Nice to Have

  • Experience with Docker, Kubernetes, and cloud-native architectures.
  • Exposure to MLOps tooling, model serving, and ML infrastructure.
  • Experience building production applications using LLMs or generative AI.
  • Knowledge of distributed systems, performance optimisation, and infrastructure automation.
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Reference: WJ-766_23773487

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