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Machine Learning Engineer

Understanding Recruitment
Nottingham
1 week ago
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Overview

🤖 Machine Learning Engineer – Applied AI for Real-World Impact

Nottingham (Hybrid, 2 days per week)

30 Days Holiday + Pension + Flexible Working

Why join?

This is your chance to engineer AI systems that matter, building and deploying models that shape decisions across healthcare, mobility, and retail. You’ll work with rich, complex datasets and take models from concept to scalable, production-ready solutions that create real-world change.

You’ll join a high-calibre, collaborative team where ownership, experimentation, and learning are encouraged. Expect to work with a modern ML infrastructure, have real influence over how AI gets deployed, and see your work make tangible impact across industries.

What you’ll do
  • Design, build, and optimise scalable ML pipelines and data workflows
  • Deploy, monitor, and maintain machine learning models in production environments
  • Collaborate with data scientists to move research prototypes into production-ready systems
  • Automate training, evaluation, and deployment processes for continuous improvement
  • Contribute to model explainability, performance tuning, and reliability
  • Communicate results and system behaviour clearly to technical and non-technical stakeholders
What we’re looking for
  • Strong academic foundation (STEM, Computer Science, or AI-related field)
  • ~2+ years’ experience as an ML Engineer, Data Engineer, or Applied ML practitioner
  • Proficiency in Python and SQL; experience with cloud platforms, ML frameworks (PyTorch/TensorFlow), and modern data tooling (Databricks, MLflow, etc.)
  • Experience productionising ML models and building robust, maintainable pipelines
  • A problem-solver with curiosity, creativity, and a passion for delivering scalable AI solutions
Why now?

This is a pivotal time to join a fast-growing AI company born from world-class academic research, now working with major brands like Boots. You’ll help scale intelligent systems that combine research-grade innovation with real-world application, all while contributing to a culture that values curiosity, autonomy, and ethical AI.


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