Senior Machine Learning Engineer, Wallet, Payment & Commerce

Apple Inc

Quick summary

Work type: On-site
Location: Austin, TX
Posted: 5 days ago
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $221k

$167k most similar roles pay here $271k

This listing doesn't post a salary. Most similar roles pay $195,100–$246,150.

Based on 239 similar postings.

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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 1723 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1398 roles with salary data.

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At a glance

TL;DR · Senior Machine Learning Engineer, Wallet, Payment & Commerce

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As a Senior Machine Learning Engineer on Apple’s Wallet, Payment & Commerce team, you will design and implement end-to-end machine learning solutions to enhance security, prevent fraud, and optimize operational efficiency across various platforms. Your daily tasks include collaborating with cross-functional teams to define problems, develop data-driven solutions, and communicate results effectively. You will own the full ML lifecycle from feature engineering to model deployment, ensuring compliance with privacy regulations while driving improvements in data operations. The role requires expertise in predictive modeling, statistical analysis, and experience with technologies like Python, Scala, Java, Hadoop, Spark, and ML frameworks such as Turi Create. This position presents unique challenges due to the scale of Apple’s business and the need for innovative approaches that protect user privacy while enhancing security features.

Skills

Python Scala Java SQL Hadoop Spark Airflow Ray Weights & Biases Turi Create ML workflow orchestration Data management tooling Privacy-preserving techniques Fraud detection Risk modeling CI/CD

What you'll do

Design and deliver end-to-end machine learning solutions for fraud prevention and security improvements.
Implement feature engineering, model training, evaluation, and performance reporting in production environments.
Lead data collection initiatives for ML programs, ensuring compliance with regulatory requirements.
Drive enhancements to data operations by reducing acquisition lead time and cost through scalable workflows.
Document and share technical knowledge on risk features, fraud modeling approaches, and decision system performance.

What we're looking for

Master's degree in Computer Science, Statistics, Machine Learning, or equivalent quantitative field.
At least five years of industry experience deploying machine learning algorithms in production environments.
Deep expertise working with relational databases, SQL, and large-scale distributed computing systems like Hadoop and Spark.
Strong programming skills in Python, Scala, Java; familiarity with Objective-C or Swift for on-device model deployment.
Experience implementing privacy-preserving techniques on production data pipelines and ML models.
Domain expertise in fraud detection, risk modeling, or security-focused machine learning applications.
Experience managing data acquisition programs, including working with external vendors and procurement teams.

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