Machine Learning Engineer (Applied AI / Scientific Computing)

  • NLP PEOPLE
  • Blackwater, Surrey
  • 09/06/2026
Full time Information Technology Telecommunications Python Software Engineer

Job Description

Company

Ion recruitment

Location

Surrey, UK (Office based)

Overview

A global software company is evolving its core engineering platforms by embedding machine learning and applied AI into high performance simulation and modelling tools used worldwide.

This is a hands on applied AI role - focused on building and deploying ML solutions inside production grade engineering systems, not isolated research or experimental prototypes.

Responsibilities
  • Create, deploy, and maintain machine learning models in production engineering software systems.
  • Own the full ML pipeline: data preparation, feature engineering, training, evaluation, and optimisation.
  • Translate complex scientific/engineering problems into ML driven solutions.
  • Improve model performance in compute intensive environments.
  • Write clean, testable, maintainable production code.
  • Integrate ML services via APIs and software components.
  • Collaborate with engineers and domain specialists on real world systems.
Required Experience and Skills
  • Strong Python programming and software engineering fundamentals.
  • Proven experience applying machine learning to real world datasets and problems.
  • Understanding of model trade offs, performance, and production constraints.
  • Experience working with complex or imperfect data.
  • Ability to write efficient, scalable, production quality code.
  • Senior level (5+ years of experience).
Desired Experience
  • PyTorch, TensorFlow, or similar ML frameworks.
  • Scientific computing, numerical methods, optimisation.
  • GPU acceleration or high performance computing.
  • MLOps, model deployment, APIs, or production pipelines.
Benefits
  • Focus on applied AI in real engineering systems.
  • Work on technically challenging, high impact problems.
  • Close collaboration with experienced engineers and domain experts.
  • Influence how AI is embedded into core global software products.
  • Long term technical depth, not short cycle ML experimentation.