ML Engineer - Evaluation Analysis, Metric and Data Strategy

Apple Inc

Quick summary

Work type
On-site
Location
Seattle, WA
Salary
$139,500–$258,100 / yr
Posted
44 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $213k
This role $199k
$125k most similar roles pay here $274k

This role pays less than 62% of similar roles. Most pay $176,337–$249,750 — the shaded band above. At the midpoint, this role pays about $199k versus about $213k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 638 open roles on FindRole.

Listed pay typically runs $171,600–$272,100 across 505 roles with salary data.

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At a glance

TL;DR · ML Engineer - Evaluation Analysis, Metric and Data Strategy

As an ML Engineer specializing in Evaluation Analysis and Metric Development at the core of the team’s analytical function, you will define quality metrics for AI features and agentic experiences, ensuring each feature has clear performance indicators. Your day-to-day involves analyzing evaluation results to identify trends and patterns, collaborating with partner teams on data collection strategies, and translating complex analysis into actionable insights for leadership. You will design comprehensive metrics frameworks, audit dataset representativeness, and deliver concise summaries that influence model development direction. The role requires proficiency in Python (pandas, scipy, scikit-learn) and a strong background in statistical methods, with experience working with production user data and understanding its biases. Ideal candidates have expertise in evaluating AI-driven features in consumer products and familiarity with agentic orchestration frameworks like LangChain and emerging interoperability protocols.

What you'll do

  • Define and own quality metrics frameworks for AI features and agentic experiences.
  • Analyze evaluation outputs to identify trends, regressions, and segment-level patterns.
  • Drive data collection strategies with partner teams to ensure real-world relevance.
  • Audit evaluation data representativeness to reflect actual user distributions accurately.
  • Deliver concise metric summaries to leadership for informed decision-making.
  • Influence model development direction by providing actionable feedback on failures.

What we're looking for

  • Bachelor’s degree in Statistics, Data Science, Applied Mathematics, Computer Science, or related quantitative field.
  • 5+ years of experience defining and operationalizing quality metrics in applied science, data science, or evaluation research.
  • Experience with statistical analysis methods including significance testing, sampling design, effect size estimation, and experimental design.
  • Proficiency in Python (pandas, scipy, scikit-learn) for data analysis and visualization.
  • Ability to design evaluation approaches where the unit of analysis is a session or conversation rather than a single model output.
  • Track record of independently designing metrics frameworks and driving data-informed decisions across cross-functional teams.

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