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Machine Learning Engineer
Gerrell & Hard Ltd.
- Oxford, England, United Kingdom
- Oxford, England, United Kingdom
About
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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Languages
- English
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