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AI / Machine LearningRemote

Staff Machine Learning Engineer

Hexwired Recruitment Limited - Recruiter

UK, ๐Ÿ‡ฌ๐Ÿ‡ง United KingdomFull-time - Lead (7-10 years)0 applicantsCloses Aug 9, 2026

Salary

GBP 160,000 - 200,000 / year

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Job description

Job details

  • Location: UK
  • Work mode: Remote
  • Employment type: Full-time (Not an internship)
  • Salary: GBP 160,000 - 200,000 per year

Role overview

Hexwired Recruitment is seeking a Staff Machine Learning Engineer for an innovative AI software company. This senior leadership role focuses on bridging the gap between theoretical research and production engineering, ensuring that cutting-edge models are scaled into robust, real-world software products.

Job details

This is a full-time, Remote position based in the UK. This is not an internship. The offered salary range is ยฃ160,000 to ยฃ200,000 GBP per year.

Responsibilities

  • Lead the transition of ML models from experimental research to production-ready systems.
  • Own the execution and technical roadmap of the company's machine learning initiatives.
  • Collaborate with research scientists to optimize model performance and scalability.
  • Implement robust MLOps pipelines to automate deployment and monitoring.
  • Mentor junior and mid-level engineers on best practices for AI engineering.

Requirements

  • Extensive experience as a Machine Learning Engineer or Technical Lead.
  • Proven track record of deploying large-scale ML models in a production environment.
  • Deep proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow.
  • Strong understanding of software engineering principles and system design.
  • Ability to operate independently in a remote-first professional environment.

Benefits

  • Competitive salary range of ยฃ160,000 - ยฃ200,000 GBP.
  • Fully remote work flexibility.
  • Opportunity to work with cutting-edge AI technology.
  • High-impact leadership role within a growing AI company.

Keywords

Machine LearningMLOpsPythonPyTorchTensorFlowModel DeploymentAI ArchitectureScalable Systems