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MLOps Engineering Manager

Unitingambition — United Kingdom · Posted ~22 hours ago

Lead Full-time Hybrid £100000-£120000+ depending on experience

Skills

MLOps Technical leadership Software architecture ML systems Backend infrastructure Frontend integration MLflow AWS SageMaker Cloud infrastructure AWS

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Summary ✨ AI‑Generated

A globally oriented organization is seeking an MLOps Engineering Manager to lead complex machine-learning transformation initiatives. The role combines technical leadership, architectural ownership, and hands-on delivery across backend infrastructure and frontend integration. You will help drive a migration from one ML lifecycle platform to a major cloud-based machine-learning service while working closely with data scientists, engineers, and cross-functional stakeholders. The position is permanent and hybrid, with regular office attendance in London.

Highlights

High-paying permanent leadership role with substantial technical ownership across machine-learning systems, architecture, infrastructure, and delivery. The position combines hands-on engineering with strategic transformation work and collaboration across technical disciplines.

Description

MLOps Engineering Manager £100,000 - £120,000+ DoE Hybrid | London | 2 x weekly office visits Permanent The Business Join a globally recognised brand with a legacy of excellence and a track record of shaping its industry. While its heritage is well established, the organisation is firmly focused on the future, making major investments across technology, data, and AI to accelerate innovation at scale. As part of this journey, they are now seeking a highly capable technical leader to help support their next phase of growth and lead complex transformation initiatives. The Role This is a combination of strong technical leadership, architectural ownership and delivery responsibility of ML systems (from backend infrastructure through to frontend integration). There is an ongoing migration from MLflow to AWS SageMaker, so you will be working closely with data scientists, engineers and cross-functional stakeholders to deliver this. You will also be responsible for MLOps delivery from predictive maintenance, fault detection, and component lifecycle optimisation, while leading and mentoring a team of engineers. You will also be working with 5-10 engineers with a slightly higher focus on people leadership (approximately 60/40 split - people leadership / hands-on). About you 10+ years in Software, Data, or ML Engineering5+ years as a Tech Lead, managing teams of 5+, owning end-to-end technical deliveryProficiency with Python and MLflowStrong AWS/cloud-native experience ( ideally with SageMaker exposure)React frontend proficiencyDocker, Kafka, and large-scale data systems (e.g. Spark) experienceStrong leadership presence and senior stakeholder communication skills If you have the technical expertise, leadership experience and ambition to make an impact at scale, please apply now. We'd be delighted to discuss the opportunity with you.