Senior Machine Learning Engineer, Commerce and Growth Intelligence
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something — you’ll add something!
The Commerce & Growth Intelligence team at Apple Services Engineering is at the forefront of delivering cutting-edge innovations that shape the entire lifecycle of a user’s journey—from account creation to marketing, personalized offers, subscription ranking, churn modeling, lifetime value optimization, and beyond. We’re solving problems of unprecedented scale and complexity, leveraging the latest advancements in machine learning and AI, including large language models (LLMs). Our team thrives in a dynamic and collaborative environment, where impactful ideas become transformative products and experiences for millions of customers worldwide
Join our innovative team to design, develop, and deploy scalable, high-volume, low-latency machine learning inference services that power customer-facing experiences. You’ll work with advanced technologies to integrate on-device machine learning with the iOS ecosystem, build big data pipelines for model training and tuning, and optimize training operations on large GPU clusters, and ensure operational reliability and observability across our platforms.
Key Responsibilities
- Inference Service Development: Design, develop, and deploy high-performance machine learning inference services with a focus on scalability and efficiency.
- On-Device ML Solutions: Architect and integrate machine learning solutions with various platforms, enhancing user experience and on-device capabilities.
- Big Data Pipeline Engineering: Build and maintain data processing pipelines to support model training and tuning across large datasets.
- Model Training Pipeline Optimization: Manage and optimize machine learning training pipelines to improve performance in distributed computing environments.
- Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Information Systems, or Electronic Engineering
- 5+ years of work experience in machine learning engineering
- Proven experience building large-scale event processing systems; a deep understanding of JVM technologies is a plus.
- Hands-on experience with on-device machine learning solutions; familiarity with iOS ecosystems (CoreML, Swift SDK) is advantageous.
- Expertise in large-volume big data processing (batch or streaming); experience with Apache and Apache Flink using Scala is a plus.
- Familiarity with training and optimizing machine learning models (e.g., XGBoost, PyTorch, LLMs) is beneficial.
- Minimum three years of experience in developing customer-facing machine learning systems is highly desirable.
- Actively engage with product teams to discuss and influence product decisions, using strong communication skills to design cohesive engineering solutions that scale ML products for billions of users and devices.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.