Machine Learning Evaluation Engineer

Apple Inc

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Sunnyvale, CA
Salary: $150,400–$277,600 / yr
Posted: 12 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $225k

This role $214k

$135k most similar roles pay here $293k

This role pays less than 52% of similar roles. Most pay $194,283–$254,750 — the shaded band above. At the midpoint, this role pays about $214k versus about $225k 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 1984 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1590 roles with salary data.

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At a glance

TL;DR · Machine Learning Evaluation Engineer

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The Machine Learning Evaluation Engineer joins the team to define and drive evaluation strategies for computer vision and machine learning algorithms used in complex product experiences. This role involves building scalable evaluation methodologies, designing metrics that go beyond aggregate accuracy, and performing deep failure analysis to identify root causes such as data quality issues or algorithm limitations. The engineer will analyze large-scale datasets to improve representation, develop automated workflows for reporting, and create visualizations to communicate performance regressions. Key technical requirements include proficiency in Python for data processing and visualization, experience with statistical modeling, and familiarity with deep learning frameworks. Candidates must demonstrate expertise in evaluating tasks like object detection and segmentation while utilizing AI-assisted tools to accelerate analysis and engineering efficiency across the machine learning development lifecycle.

Skills

Machine Learning Computer Vision Python Data Analysis Statistical Modeling Deep Learning Data Pipelines Visualization Synthetic Data Data Augmentation Model Monitoring Generative AI Root-Cause Analysis Evaluation Frameworks

What you'll do

Define and drive evaluation strategies for computer vision and machine learning algorithms.
Design metrics and methodologies that identify performance across specific data slices and scenarios.
Analyze large-scale datasets to identify gaps in data quality, coverage, and representativeness.
Perform failure analysis to identify recurring patterns and determine root causes of model issues.
Build tools and visualizations to help engineers explore failures and understand underlying causes.
Develop scalable, automated workflows for evaluation, analysis, and reporting using AI-assisted tools.
Translate technical findings into actionable recommendations to influence algorithm and data decisions.

What we're looking for

Bachelor of Science degree required.
At least 3 years of relevant industry experience in machine learning, computer vision, or data science.
Strong background in classical machine learning and statistical modeling techniques.
Proven experience designing evaluation methodologies and quality metrics for ML algorithms.
Expertise in failure analysis to identify systematic model weaknesses and provide actionable recommendations.
Experience analyzing large-scale datasets for quality, diversity, and coverage gaps.
Proficiency in Python for data processing, analysis, and visualization.
Experience building automated, scalable evaluation pipelines and using AI-assisted tools for engineering efficiency.

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