Machine Learning Engineer - iCloud Anti-Abuse

Apple Inc

Quick summary

Work type: On-site
Location: San Diego, CA
Salary: $139,500–$258,100 / yr
Posted: 21 days ago

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $211k

This role $199k

$125k most similar roles pay here $272k

This role pays less than 57% of similar roles. Most pay $172,500–$249,750 — the shaded band above. At the midpoint, this role pays about $199k versus about $211k for comparable roles.

Based on 239 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 969 open roles on FindRole.

Listed pay typically runs $163,300–$272,100 across 756 roles with salary data.

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At a glance

TL;DR · Machine Learning Engineer - iCloud Anti-Abuse

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As an ML engineer on Apple's iCloud Anti-Abuse team, you will play a critical role in protecting millions of users from spam and phishing by designing, training, and deploying machine learning models that operate at massive scale. Your responsibilities include managing the entire lifecycle of abuse detection systems, from data pipelines to real-time inference, ensuring low-latency and high availability. You will collaborate closely with backend engineers and cross-functional teams to build robust ML infrastructure and continuously improve model performance through analysis and iterative development. The ideal candidate has 3+ years of hands-on experience in machine learning engineering, proficiency in languages like Python or Java, expertise in distributed systems, and a solid understanding of classification and ranking techniques. Experience with abuse detection and NLP is preferred, as you will work on cutting-edge solutions to prevent malicious content from reaching users.

Skills

Python Java Scala Kotlin Go AWS Azure GCP Kubernetes Docker CI/CD Terraform PostgreSQL MySQL Redis Spark Hadoop TensorFlow PyTorch Scikit-learn NLP MLflow

What you'll do

Design and maintain end-to-end ML pipelines for abuse detection.
Develop low-latency, high-availability ML infrastructure at scale.
Identify and score abusive actors and patterns using advanced techniques.
Analyze model performance to drive continuous improvements in user protection.
Collaborate with cross-functional teams to integrate ML models into production systems.

What we're looking for

3+ years of hands-on machine learning engineering experience
Strong programming skills in production languages like Java, Python, etc.
Experience building and operating ML pipelines from data to monitoring
Solid foundation in distributed systems with scalability expertise
Familiarity with classification, ranking, or anomaly detection techniques
Ability to independently drive projects through the full lifecycle
BS degree in Computer Science, Machine Learning, or related field