MLOps Engineering Manager

Uniting Ambition; Greater London; Hybrid; GBP 100,000 - 120,000; Full time

Job summary

Uniting Ambition is seeking an MLOps Engineering Manager to lead ML systems from backend infrastructure to frontend integration in a hybrid London setting. You will guide architecture, deliver MLops projects, and collaborate with data scientists and engineers for migrating from MLflow to SageMaker.

The role demands 10+ years in software/data/ML, 5+ years as a tech lead, and strong Python, AWS/SageMaker, and React experience. You will manage 5–10 engineers with a 60/40 people/hands-on split.

Qualifications

• 10+ years in Software, Data, or ML Engineering
• 5+ years as a Tech Lead, managing teams of 5+
• Proficiency with Python and MLflow
• Strong AWS/cloud-native experience (ideally with SageMaker exposure)
• React frontend proficiency
• Docker, Kafka, and large-scale data systems (e.g. Spark) experience
• Strong leadership presence and senior stakeholder communication skills

Responsibilities

• Provide technical leadership and architectural ownership for ML systems
• Lead migration from MLflow to AWS SageMaker with cross-functional teams
• Deliver MLOps including predictive maintenance, fault detection, and lifecycle optimisation
• Mentor and manage a team of 5-10 engineers with a 60/40 focus on people leadership/hands-on

Skills

Python

MLflow

AWS

SageMaker

React

Docker

Kafka

Spark

Leadership

Tools

MLflow

AWS

SageMaker

Docker

Kafka

Spark

React

Job 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 Engineering
• 5+ years as a Tech Lead, managing teams of 5+, owning end-to-end technical delivery
• Proficiency with Python and MLflow
• Strong AWS/cloud-native experience ( ideally with SageMaker exposure)
• React frontend proficiency
• Docker, Kafka, and large-scale data systems (e.g. Spark) experience
• Strong leadership presence and senior stakeholder communication skills

We'd be delighted to discuss the opportunity with you