ML Engineer: Intelligent Quality Systems

Apple Inc.; Cupertino (CA); On-site; USD 150,000 - 278,000; Full time

Job summary

Apple Inc. Cupertino, CA is seeking a Machine Learning Engineer for the Intelligent Quality Systems team to design and deploy ML-powered solutions that improve software quality at scale.

You will prototype algorithms for change-impact, failure analysis, and multimodal test validation, turning research ideas into production systems used by hundreds of millions of users. You will collaborate with researchers and software engineers, build data collection and evaluation pipelines, and help ensure

Qualifications

• 3+ years of ML experience in academic or professional settings.
• Strong programming and software engineering, producing production-quality code.
• Solid understanding of ML fundamentals, model training, evaluation, and debugging.
• BS or MS in CS, ML, statistics, or related field.

Responsibilities

• Implement and refine ML solutions across testing lifecycle, test selection, failure triage, visual validation, and test coverage analysis
• Rapidly prototype multiple algorithmic approaches to identify the most promising directions
• Design and implement data collection, labeling, and evaluation strategies for training and measuring ML systems
• Work with large-scale test result and code change data to surface patterns and inform modeling decisions
• Proactively identify research-to-production gaps and technical risks in proposed ML solutions
• Collaborate with applied scientists and software engineers to ship reliable, high-impact ML systems

Skills

ML fundamentals

Programming

Software engineering

ML deployment

Education

BS/MS in CS/ML/Stats

Tools

CI/CD systems

Data pipelines

LLMs

Job description

Apple Inc. Cupertino, CA is seeking a Machine Learning Engineer for the Intelligent Quality Systems team to design and deploy ML-powered solutions that improve software quality at scale.

You will prototype algorithms for change-impact, failure analysis, and multimodal test validation, turning research ideas into production systems used by hundreds of millions of users. You will collaborate with researchers and software engineers, build data collection and evaluation pipelines, and help ensure