Lead Quality Assurance Engineer

Accountabilities:

• 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.

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.


• Bonus: experience applying ML/AI in sports analytics or similar data-driven domains.

Benefits

• Competitive salary range of £76,000 – £127,000 GBP, with long-term incentive (LTI) eligibility.


• Flexible working arrangements, including remote options within the UK or hybrid access to a London office.


• Work-life balance support, including flexible vacation policies and meeting-free focus time.


• Strong career development support, with learning resources and growth opportunities.


• Comprehensive wellbeing support, including mental health resources and employee assistance programs.


• Inclusive and collaborative culture focused on autonomy, trust, and engineering excellence.


• High-impact work contributing to globally used sports technology and AI-driven insights.


• Modern engineering environment with access to advanced tools and infrastructure.

This listing is from ats_lever. View original listing ↗