ML Engineer - Automated Evaluation and Adversarial Design

The Productivity and Machine Learning Evaluation team ensures the quality of AI-powered features across a suite of productivity and creative applications - including Creator Studio - used by hundreds of millions of people. This team serves as the primary evaluation function, providing critical quality signals that directly influence model development decisions and product launches.

This role focuses on building and scaling automated evaluation systems and designing adversarial and stress-testing methodologies across multiple AI features. The work requires a deep understanding of how AI systems fail and how to measure quality rigorously. This is an opportunity to shape the evaluation infrastructure that determines whether AI features meet the bar for hundreds of millions of users.

Description

Day-to-day work involves designing, building, and maintaining automated evaluation systems that assess AI feature quality at scale. This includes creating adversarial test suites that probe model weaknesses and running stress tests to ensure features perform under demanding conditions. The role requires close collaboration with cross-functional partners to ensure evaluation methods are well-calibrated and integrated into development workflows.

Typical deliverables include: evaluation frameworks and rubrics, quality assessment reports, adversarial test case libraries, and recommendations on model readiness.","responsibilities":"Define and own the automated evaluation approach for AI features, translating qualitative notions of quality into measurable, reproducible assessments

Build adversarial test suites that target known and emerging model failure modes, including edge cases relevant to productivity application workflows

Develop and execute stress test protocols that validate minimum performance thresholds under atypical input conditions

Ensure alignment between automated and human evaluation methods on an ongoing basis, identifying and resolving systematic disagreements

Collaborate with engineering partners to integrate evaluation into development and release workflows

Scale adversarial test case generation and stress test execution, leveraging automation where appropriate

Influence model and feature quality decisions by communicating evaluation findings and readiness assessments to cross-functional partners

Preferred Qualifications

Experience evaluating user-facing AI features in consumer applications, with an understanding of how technical metrics connect to user-perceived quality

Familiarity with productivity software or creative tools, with the ability to assess output quality from a user workflow perspective

Experience ensuring alignment between automated and human evaluation methods, including inter-annotator agreement analysis and bias detection

Track record of designing evaluation systems that scale across multiple features or product areas without requiring bespoke solutions for each

Experience evaluating different types of AI systems, including API-based and custom-trained models

Demonstrated ability to communicate evaluation findings and readiness assessments to cross-functional partners

Experience leveraging automation to scale evaluation data generation and analysis

Graduate degree in a relevant field

Minimum Qualifications

Bachelor's degree in Computer Science, Machine Learning, Statistics, or a related field

4+ years of experience building or significantly extending ML evaluation systems, including designing evaluation benchmarks or quality assessment frameworks

Experience independently defining evaluation architecture and methodology for AI or ML systems

Experience designing adversarial or red-teaming test methodologies for ML models or AI-powered features

Experience with Python and ML frameworks (PyTorch, TensorFlow, or equivalent) in production or near-production settings

Track record of owning technical direction for evaluation efforts across multiple features or product areas

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .