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Staff Machine Learning Engineer - Ops

Wayve · London, United Kingdom

Publicada em 06/10/2026

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Before the detail, here's the challenge you'd help us solve.We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that.Here’s what this particular role covers.🛠️ About our Model Integration and Release Team Our Model Integration and Release team owns the engineering release process for Wayve’s driving models. When research and engineering teams develop new architectures, features, or data changes, we validate that they meet our quality, safety, and performance standards before they reach customers. The team works across ML engineering, AI Platform, evaluation, and CI/CD to protect the model baseline while continually improving how reliably and efficiently we deliver models.⁠ 🧠 Your day-to-dayDefine and evolve Wayve’s model development and release processes, including branching strategies, release cadence, configuration management, and quality gates. Review proposed model, architecture, code, and metric changes to ensure the implementation matches its intended outcome. Assess evaluation results and determine whether releases meet Wayve’s quality and safety standards. Identify delivery bottlenecks and work across teams to address their root causes. Balance speed and rigour, making informed decisions about when to accelerate delivery and when a release needs further validation. 🧩 What you’ll be working onRelease pipelines covering the full ML training and delivery lifecycle. Automated checks and tooling that identify issues earlier in development. Reliable evaluation methods for assessing model changes and release readiness. CI/CD workflows that streamline model integration and delivery. Monitoring and observability that improve confidence in production releases. Engineering standards and operational processes that enable teams to deliver high-quality ML systems at scale. 🙌 You should apply ifYou have signi
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