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About the Role

Join Apple's HID Quality Engineering team to ensure our products exceed customer expectations. You will work with QE and Algorithm teams to build metrics around algorithm performance, turning user behavior into quality specifications and measurable standards. You will validate new customer-facing algorithms effectively using data and repeatable processes, including defining the right data, ensuring data quality and labeling, and running tests on datasets.

Responsibilities

• Define algorithm quality.
• Write quality specifications.
• Establish benchmarks.
• Develop test scenario frameworks.
• Partner with algorithm, platform, and UX research teams to identify quality standard gaps.
• Define the right data for validation.
• Ensure quality of data and labeling.
• Run tests on datasets.

Requirements

• BS in EE, ECE, CS, Statistics, HCI, Cognitive Science, or a related field.
• 3+ years of experience in quality engineering, test strategy, or algorithm/ML evaluation.
• Experience writing quality specifications or test plans for complex technical systems adopted by multiple teams.
• Experience with signal-level sensor algorithms.
• Familiarity with statistical methods used in algorithm evaluation (e.g., A/B testing, regression analysis, significance testing).
• Working proficiency with Python for data exploration and analysis.
• MS or PhD in EE, ECE, CS, Statistics, HCI, Cognitive Science, or a related field.
• Strong understanding of ML and sensing system behavior, with the ability to reason about failure modes, edge cases, and the difference between a metric shifting and quality actually changing.
• Experience defining test scenario coverage models and setting benchmarks for systems where ground truth is ambiguous or user-dependent.
• Experience building consensus on quality standards across teams with competing priorities.
• Ability to write specifications precise enough for engineers to implement automation directly, without ambiguity.
• Background in UX research, HCI, or human factors, with experience grounding technical quality definitions in human behavior.
• Familiarity with embedded platform constraints.
• Experience with causal inference or advanced experimental design for algorithm evaluation.

Skills

• Quality Engineering
• Test Strategy
• Algorithm Evaluation
• ML Evaluation
• Signal-level sensor algorithms
• Statistical methods
• A/B testing
• Regression analysis
• Significance testing
• Python
• Data exploration
• Data analysis
• ML
• Sensing system behavior
• Test scenario coverage models
• UX research
• HCI
• Human factors
• Embedded platform constraints
• Causal inference
• Experimental design

Experience Level

• 3+ years of experience

Education Level

• BS in EE, ECE, CS, Statistics, HCI, Cognitive Science, or a related field
• MS or PhD in EE, ECE, CS, Statistics, HCI, Cognitive Science, or a related field

About the Company

• Apple's HID Quality Engineering team