ML Engineer: Materials Innovation & Hybrid MLOps

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

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.