Machine Learning Engineer

Gerrell & Hard Ltd.
Oxford
2 months ago
Applications closed

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Machine Learning Engineer
Oxford – Some flexibility on the working times and potential for some hybrid working for the right candidate
£Competitive + excellent benefits


Join a fast-growing, venture-funded technology company developing the next generation of advanced materials. Our multidisciplinary team of metallurgists, engineers, and software developers works across the UK, Japan, and the US, using cutting‑edge machine learning and physical modelling to accelerate materials innovation and transform manufacturing.


Role Overview

We are seeking a Machine Learning Engineer to design, develop, and validate novel ML models that optimise manufacturing processes and material composition. You will collaborate closely with process engineers and materials scientists, identifying meaningful features and translating complex datasets into impactful insights. You will also help advance our internal ML platforms to support model adoption and scale.


In this role, you will:

  • Build robust ML and MLOps pipelines for scalable, reproducible model development, deployment, and monitoring.
  • Use tools such as Airflow for workflow orchestration and MLflow for experiment tracking, model registry, and lifecycle management.
  • Work within an agile development environment and help prioritise high-value opportunities for rapid delivery.

Essential Skills

  • Bachelor’s degree (2:1 or above) in a STEM field
  • Strong Python development skills
  • Hands‑on experience developing ML and/or deep learning models for scientific or engineering problems
  • Experience with MLOps tools such as Airflow, MLflow, and containerisation (e.g., Docker)
  • Strong data‑visualisation and storytelling skills
  • Interest in materials discovery, computer vision, big data, or optimisation
  • Collaborative communicator, organised, proactive, and curious

Desired Skills

  • Master’s degree in ML, mathematics, or statistics
  • Knowledge of probabilistic and Bayesian modelling
  • Solid software‑engineering principles and experience with an OO language
  • Familiarity with cloud platforms (Azure, AWS, or GCP) and IaC tools such as Terraform


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