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Engineering Manager - MLOps & Edge Infrastructure
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The role
Lead a London-based team bridging state-of-the-art AI research and edge devices.
Own the pipeline from cloud to edge, re-architecting model deployment for thousands of devices and transitioning to granular, dynamic delivery.
Design and implement Shadow Mode infrastructure to test candidate models on production devices before full rollout.
Build tooling for governance, monitoring model drift, performance, and edge-health signals across varied environments.
Hire, mentor, and grow Senior to Mid-level engineers, fostering technical excellence and agile delivery.
Collaborate with the Embedded squad in the Netherlands and the London AI/ML organization to remove friction between training and inference.
Own the pipeline from cloud to edge, re-architecting model deployment for thousands of devices and transitioning to granular, dynamic delivery.
Design and implement Shadow Mode infrastructure to test candidate models on production devices before full rollout.
Build tooling for governance, monitoring model drift, performance, and edge-health signals across varied environments.
Hire, mentor, and grow Senior to Mid-level engineers, fostering technical excellence and agile delivery.
Collaborate with the Embedded squad in the Netherlands and the London AI/ML organization to remove friction between training and inference.
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