The Machine Learning Evaluation Engineer will define and drive the evaluation of advanced machine learning and computer vision technologies. This role involves collaborating with algorithm, data, and engineering teams to build scalable evaluation methodologies and uncover model weaknesses. The ideal candidate will have a strong background in classical machine learning and computer vision, along with hands-on experience in metrics design and data analysis. The engineer will also be responsible for developing automated workflows for evaluation and reporting.

• BS and a minimum of 3 years relevant industry experience in machine learning, computer vision, algorithm evaluation, data science, or a related field.
• Strong background in machine learning and computer vision, including classical ML and statistical modeling techniques.
• Proven experience designing and implementing evaluation methodologies and quality metrics for ML algorithms.
• Strong expertise in failure analysis and root-cause analysis.
• Strong programming skills in Python with experience in data processing, analysis, and visualization.
• Experience with large-scale ML datasets and data pipelines.
• MS in Computer Science, Computer Engineering, Electrical Engineering, Statistics, Applied Mathematics, or a related technical field is a plus.

• Define and drive the evaluation strategy for computer vision and machine learning algorithms.
• Design metrics and evaluation methodologies that help understand performance across important data slices.
• Analyze large-scale datasets to identify gaps in data quality and coverage.
• Investigate model failures and develop failure taxonomies.
• Build tools and visualizations that enable engineers to explore failures efficiently.
• Develop scalable and automated workflows for evaluation, analysis, and reporting.
• Shape evaluation best practices and influence algorithm and data decisions.

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.