# Lead Quality Assurance Engineer - Machine Learning

**Company:** [Hudl](https://hotfix.jobs/companies/hudl)
**Location:** London, United Kingdom
**Role:** QA Engineering
**Salary:** £76k – £127k/yr
**Experience:** 5+ years
**Skills:** MLOps, Machine Learning, Platform Engineering, CI/CD, Test Automation, Canary Releases, A/B Testing, Automated Rollback, Observability, Model Deployment, Inference Systems, Hardware-In-The-Loop Testing, Distributed Systems, Python, Quality Engineering
**Posted:** 2026-08-14

> Leads quality strategy and hands-on engineering for a shared MLOps platform, building test frameworks, deployment safety tooling, and observability systems. The role requires strong platform engineering expertise, technical leadership, and experience guiding teams across complex ML systems.

## Job Description

## Responsibilities
- Provide technical leadership across the Applied Machine Learning Platform squad and broader AML organization, helping teams ship ML products faster, safer, and with greater confidence from model development through scaled inference.
- Own the architecture and long-term strategy for quality infrastructure across the MLOps platform.
- Design and build test frameworks, deployment safety tooling, and observability solutions.
- Drive alignment across AML squads on CI/CD pipeline standards, canary release patterns, and hardware-in-the-loop testing.
- Write code, design systems, and implement quality solutions as a hands-on contributor.
- Anticipate risks across experimentation, deployment, inference, and observability to prevent production issues.
- Coach and mentor Software Engineers, Data Scientists, and QA practitioners on technical quality and innovation.

## Requirements
- Hands-on experience designing and building shared ML platform tooling, including experimentation infrastructure, model deployment pipelines, observability systems, or inference at scale.
- Experience leading complex quality initiatives across platform and product teams.
- Deep understanding of CI/CD pipelines and deployment safety patterns such as canary releases, A/B testing, and automated rollback.
- Ability to influence and guide teams without direct reporting authority.
- Ability to identify and solve quality challenges across complex, distributed ML systems.
- Strong remote collaboration skills across U.S. and European teams.

## Nice-to-haves
- Experience using AI/ML in the sports industry to generate data or create insights.

## Compensation and Benefits
- Base salary range: £76,000–£127,000 GBP.
- Eligible for a long-term incentive award.
- Potential bonuses based on individual and company performance.
- Flexible vacation time, company-wide holidays, and meeting-free days.
- Remote work options.
- Professional development resources and opportunities.
- Medical and retirement benefits depending on location.
- Employee Assistance Program and employee resource groups.

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