Lead, Machine Translation Quality Engineering

Apple, Inc.; Seattle (WA); On-site; USD 226,000 - 338,000; Full time

Benefits offered by this job

Medical and dental coverage

Retirement benefits

Employee stock programs

Relocation assistance

Job summary

Apple seeks a seasoned Quality Engineering Manager to lead the Translation and Machine Intelligence QE efforts in Seattle. You’ll define test strategy, mentor SDETs, and partner with software engineering, PMs, and stakeholders to ship high-quality multilingual products.

You’ll drive automation, assess performance and accuracy across iOS/macOS ecosystems, and ensure robust release readiness for client, server, and model components with a strong emphasis on collaboration and process improvements.

Qualifications

• 5+ years in quality/test engineering with leadership experience.
• Proven ability to define test strategy for mission-critical SDKs/APIs.
• Strong written and verbal communication skills.
• Creative problem solving with meticulous attention to detail.
• Proficiency with Apple operating systems and AI/ML testing contexts.

Responsibilities

• Lead a team of SDETs and Quality Engineers to validate functionality, performance and accuracy across Apple’s hardware ecosystem.
• Participate in defining testing strategies and methodologies to enhance overall software quality.
• Collaborate with developers, engineering program managers, and partner QA teams to ensure comprehensive test coverage.
• Oversee automation initiatives and testing processes for translation and AI features.

Skills

Quality Engineering Leadership

Test strategy development

Team leadership

Excellent communication

Attention to detail

Tools

Python scripting

Job description

Apple seeks a seasoned Quality Engineering Manager to lead the Translation and Machine Intelligence QE efforts in Seattle. You’ll define test strategy, mentor SDETs, and partner with software engineering, PMs, and stakeholders to ship high-quality multilingual products.

You’ll drive automation, assess performance and accuracy across iOS/macOS ecosystems, and ensure robust release readiness for client, server, and model components with a strong emphasis on collaboration and process improvements.