Production ML Engineer | Move Models to Live in Glasgow

The Opportunity Hub UK Ltd; Glasgow; Hybrid; GBP 46,000 - 70,000; Full time

Benefits offered by this job

Salary range £45,500 to £70,000

Private medical insurance

Pension contribution

Hybrid working

Bonus scheme

Annual leave

Job summary

The Opportunity Hub UK Ltd in Glasgow is seeking a Machine Learning Software Engineer to translate research into production systems. You will design end-to-end ML pipelines, deploy models, and work closely with data engineers and product teams to turn vague requirements into robust, scalable solutions.

Expect hands-on Python development, strong ML modeling experience (3+ years), and a pragmatic approach to shipping reliable systems. Hybrid work model and competitive compensation are offered.

Qualifications

• Solid commercial experience building and deploying machine learning models.
• Strong Python skills with knowledge of PyTorch or TensorFlow.
• Understanding of cloud infrastructure (AWS, Azure or GCP) for ML workloads.
• Ability to explain technical trade-offs to non-engineers.

Responsibilities

• Design and build machine learning pipelines that go into production.
• Write clean, maintainable Python code for other engineers.
• Take models from research through deployment and monitor live performance.
• Collaborate with data engineers and product teams to turn vague requirements into working systems.
• Debug model drift and data quality issues; bridge training and real-world results.
• Document approaches clearly for future handovers.

Skills

ML model deployment

Python

PyTorch

TensorFlow

MLOps

Cloud platforms

Tools

PyTorch

TensorFlow

Job description

The Opportunity Hub UK Ltd in Glasgow is seeking a Machine Learning Software Engineer to translate research into production systems. You will design end-to-end ML pipelines, deploy models, and work closely with data engineers and product teams to turn vague requirements into robust, scalable solutions.

Expect hands-on Python development, strong ML modeling experience (3+ years), and a pragmatic approach to shipping reliable systems. Hybrid work model and competitive compensation are offered.