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Machine Learning Evaluation Engineer

Apple· Hardware
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Sunnyvale, CA$150.4k - $277.6kFull-timePosted 1mo ago

About the role

Machine Learning Evaluation Engineer to define and drive evaluation of advanced ML and computer vision technologies. Build scalable evaluation methodologies, uncover model weaknesses, and provide actionable insights to ensure high-quality, robust ML systems across diverse real-world scenarios. Focus on metrics design, data analysis, failure analysis, visualization, and evaluation infrastructure, with use of AI-assisted tools to improve efficiency.

Responsibilities

  • - Define and drive the evaluation strategy for computer vision and ML algorithms used in complex product experiences.
  • - Work with algorithm engineers to understand system behavior, identify meaningful quality signals, and develop evaluation frameworks that reflect real-world performance.
  • - Design metrics and evaluation methodologies that go beyond aggregate accuracy and analyze performance across data slices and scenarios.
  • - Analyze large-scale datasets to identify gaps in data quality and coverage and improve representativeness of training/evaluation data.
  • - Conduct failure analysis, develop failure taxonomies, and determine root causes across data, labeling, algorithm limitations, environments, or system factors.
  • - Build tools and visualizations enabling engineers to explore failures and root causes.
  • - Develop scalable and automated workflows for evaluation, analysis, and reporting.
  • - Leverage AI-assisted tools to accelerate data analysis, visualization, coding, and workflow automation while maintaining rigor and reproducibility.
  • - Shape evaluation best practices and influence algorithm/data decisions across the ML development lifecycle.
  • - Collaborate with cross-functional teams to deliver high-quality ML systems.

Qualifications

  • - BS and a minimum of 3 years relevant industry experience
  • - 3+ years in machine learning, computer vision, algorithm evaluation, data science, or related field
  • - Strong background in ML and computer vision, including classical ML and statistical modeling
  • - Proven experience designing and implementing evaluation methodologies and quality metrics for ML algorithms
  • - Strong expertise in failure analysis and root-cause analysis with actionable recommendations
  • - Experience analyzing data quality, diversity, representativeness, and coverage gaps on large/complex datasets
  • - Strong Python programming skills for data processing, analysis, and visualization
  • - Experience building automated and scalable evaluation pipelines and tooling
  • - Ability to develop clear visualizations and dashboards communicating model performance, regressions, and failure patterns
  • - Strong understanding of statistical analysis, experimentation, and performance measurement
  • - Ability to independently drive ambiguous technical problems from definition through analysis and recommendations
  • - Experience using AI-powered development and analysis tools to improve productivity and workflows

Skills

Required:PythonEvaluation methodologiesFailure analysis/root-cause analysisData quality and representativeness analysisVisualization and dashboards
Nice to have:ML/DL frameworks

Benefits

  • - Comprehensive medical and dental coverage
  • - Retirement benefits
  • - Discounts on products and free services
  • - Educational expense reimbursement including tuition
  • - Potential discretionary bonuses or commission payments and relocation support
  • - Apple employee stock programs including discretionary RSU awards and Employee Stock Purchase Plan
Last updated Sep 4, 2026. Interested? Apply on the company site.

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