Machine Learning Engineer

Gerrell & Hard Ltd.; Oxford; Hybrid; GBP 150,000 - 200,000; Full time

Job summary

A leading technology firm in Oxford is seeking a Machine Learning Engineer to design and develop ML models that optimise manufacturing processes. The ideal candidate will have a Bachelor's degree in a STEM field, strong Python skills, and experience with MLOps tools. This role offers competitive compensation and flexibility in working arrangements, making it suitable for candidates interested in materials discovery and engineering innovation.

Benefits

Competitive salary

Excellent benefits

Qualifications

• 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.
• Experience with MLOps tools such as Airflow and MLflow.
• Strong data-visualisation and storytelling skills.
• Interest in materials discovery, computer vision, big data, or optimisation.

Responsibilities

• Design, develop, and validate ML models for manufacturing processes.
• Build robust ML and MLOps pipelines for scalable development.
• Collaborate closely with process engineers and materials scientists.

Skills

Python development

MLOps tools (Airflow, MLflow, Docker)

Data visualisation and storytelling

Collaboration

Education

Bachelor’s degree in a STEM field

Master’s degree in ML, mathematics, or statistics

Tools

Airflow

MLflow

Docker

Job description

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