Senior ML Ops Engineer

About the role

Senior MLOps Engineer Overview of job This role is part of our Global:IQ team, the group developing our new intelligence platform. Global:IQ brings together a suite of 1st party and partner data, tools and capabilities to turn data into audience understanding and optimised, data-led media plans. Using a combination of data science, machine learning & AI techniques, it supports smarter targeting across Global's audio and out-of-home inventory, optimises advertising creatives and automates the tracking of outcomes for advertisers through the acquisition funnel-from building awareness and consideration to driving action. As a Senior MLOps Engineer you will play a critical role in building the operational infrastructure that brings AI and ML models into production at Global:IQ. You will own the platforms, pipelines and processes that enable Data Science and Applied ML teams to deploy, monitor, retrain and govern models reliably at scale across our ad-targeting, creative optimisation and advertising measurement capabilities. This position demands a hands-on engineer with deep expertise in operationalising machine learning systems, a strong understanding of cloud infrastructure, ML lifecycle management, and production monitoring. You will work closely with Data Scientists, Data Engineers and Product teams to create robust, scalable and maintainable MLOps workflows-starting from the ground up. The role reports to the Lead Engineer (MLOps & AI) and is a unique opportunity to establish MLOps best practices in a truly innovative AI/ML & data-driven product environment. 3 best things about the job Build from Zero: You're not maintaining legacy systems-you're establishing the MLOps patterns, tooling and standards that will scale with the team for years to come. AI at the Core: This is a true AI/Data-driven product. ML isn't a nice-to-have feature - it's the product. Your infrastructure directly enables business value. Truly Cross-functional: the Global:IQ team is a tight collaboration between technical and commercial areas. Measures of success In the first few months, you would have: Defined a clear operating model between Data Engineering/MLOps and teams responsible for model development. Onboarded key 1st and 3rd party datasets following existing ingestion patterns/standards. Delivered an initial end-to-end MLOps path for at least one production ML use case, from model handoff through deployment, monitoring and rollback. Established baseline operational standards including model versioning, environment management, deployment patterns and handover processes between Data Science and Engineering. Implemented monitoring and alerting for production ML workloads, covering operational health, data quality and model performance signals. Defined a clear operating model and interfaces between teams developing models and teams operating them in production. Built collaborative relationships with Data Science, Data Engineering and Product stakeholders, demonstrating pragmatic judgement and delivery pace. Key Responsibilities of the Role ML Infrastructure & Deployment (40%) Design, build and maintain automated pipelines for model training, validation, packaging and deployment across development, staging and production environments. Implement model registries, experiment tracking and versioning systems to ensure reproducibility and traceability. Build and operationalise batch, streaming and near-real-time inference services depending on product requirements. Create reusable patterns and self-serve tooling that enable Data Science teams to deploy models independently while adhering to operational standards. Implement infrastructure for feature engineering pipelines, feature stores, and consistent serving layers between training and inference. Model Monitoring & Operations (30%) Implement comprehensive monitoring for ML workloads including prediction latency, throughput, error rates, input data quality and feature drift. Build alert

Benefits

Additional Information

Accepting applications until: 10 July 2026 Job Description We are Global We're proud to be one of the world's leading media and entertainment groups. Whether it be on-air, via global player or through our outdoor advertising, we entertain and reach over 50 million individuals across the UK every week. Across our entire business, we're committed to making more moments that matter for our audiences, customers and for each other. And every moment matters...the small, the big and everything in between. We couldn't do any of it without our talented, passionate Globallers. Everything we do is driven by our culture and the talented people who make it happen. Here at Global, we have a saying...it's all about how you make people feel. It's our company ethos, our guiding belief and it's so much more than words. It's the vibe you get when you walk into one of our offices, it's what keeps us honest and true to who we are, and above all, it's the reason we all love to work here.

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