Lead Quality Assurance Engineer
New
UKFull-TimeLead
Salary76,000 - 127,000 GBP per year
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Job Details
- Required Skills
- Machine LearningCI/CDMLOpsDistributed Systems
Requirements
- Proven experience leading quality engineering initiatives across platform, infrastructure, or product engineering teams in complex technical environments.
- Strong expertise in CI/CD pipelines, release engineering, and deployment safety patterns such as canary releases, A/B testing, and automated rollback strategies.
- Hands-on experience with MLOps, platform engineering, or large-scale distributed ML systems, including deployment and observability tooling.
- Strong understanding of software quality principles applied to production systems, including testing strategies and system reliability engineering.
- Ability to influence and mentor cross-functional teams without direct reporting lines, fostering a culture of quality and automation.
- Strong problem-solving skills with the ability to navigate complex distributed systems and identify root causes across platform layers.
- Experience working in global, distributed teams across multiple time zones.
Responsibilities
- Lead quality strategy and technical direction across the MLOps platform, ensuring scalable, reliable, and efficient delivery of ML-powered products.
- Design and evolve quality infrastructure, including test frameworks, deployment safety tooling, and observability systems across distributed ML systems.
- Define and implement CI/CD quality standards, including canary deployments, automated rollback mechanisms, and release validation practices.
- Drive proactive quality engineering by identifying risks across the ML lifecycle and preventing production issues before they occur.
- Collaborate with multiple engineering squads to align on shared quality practices and ensure consistent platform-wide standards.
- Contribute hands-on to engineering delivery, including coding, system design, and implementation of platform quality solutions.
- Mentor and coach engineers, QA practitioners, and data scientists to elevate quality engineering practices across the organization.
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