Machine Learning Engineer

Summary

At Apple, we work every day to create products that enrich people's lives. Our Apple Ads group makes it possible for people around the world to easily access informative and imaginative content on their devices while helping publishers and developers promote and monetize their work. Today, our technology and services power advertising in the App Store, Apple Maps, and Apple News. Our platforms are highly-performant, deployed at scale, and setting new standards for enabling effective advertising while protecting user privacy. The Apple Ads Machine Learning Platform team's mission is to empower Ads teams to build and scale the innovative ML systems that deliver highly optimized advertising content to consumers. Are you a results-oriented and versatile engineer who can excel in a fast-paced environment? You will work closely with ML engineers and scientists to design, develop, and build world-class platform capabilities that will enable Ads teams to improve and scale our ML features, models, and applications.

Minimum Qualifications

MS in Computer Science or related field with industrial internship experience in machine learning; or BS in Computer Science or related field with 2+ years of industrial engineering experience including 1+ years of machine learning experience Passionate about improving the developer experience for AI/ML practitioners Good understanding of the ML lifecycle: training, evaluation, deployment and serving/inferencing, with working experience building and deploying models Working knowledge of deep learning architectures and training frameworks such as PyTorch or TensorFlow Strong problem solving, debugging and performance tuning skills Results oriented, with the ability to communicate effectively, both written and verbal, with technical and non-technical multi-functional teams

Preferred Qualifications

Prior experience applying ML at scale in advertising, recommender systems, information retrieval or related domains Experience in advertising industry Good understanding of model evaluation, train-serve skew and data drift Product-minded with a proven ability to seek projects with a sense of ownership Experience with distributed training and/or optimizing large-scale models for low-latency serving Experience building infrastructure for diverse sets of model development use cases including LLMs, multimodal models, classical ML, and reinforcement learning. Experience building and/or operationalizing foundation models Experience with agentic AI Prior experience in privacy-preserving ML

Description

The ML Platform team is responsible for bringing numerous features to advertisers and consumers while simultaneously supporting scalable modeling and continuous experimentation by all Ads teams. As a key contributor to this team, you will design and develop secure and scalable back-end systems. You will enjoy building high-performing, elegant systems from the ground up, in close partnerships with various teams. You will also possess keen judgment in selecting technologies and building the right solutions for the unique ad network challenges we face. You will play a meaningful role building machine learning products which deliver on Apple's privacy commitments and change the way advertising works with data. Join us and contribute to a culture that emphasizes reliability, simplicity, and scalability. You will join a team of world-class machine learning engineers hungry to apply leading-edge technologies to deliver extraordinary experiences to our customers. We are one team, nurturing each other's growth and supporting each other in delivering for our customers!

Responsibilities

Experience writing mission-critical code for production machine learning systems Experience building ML infrastructure, frameworks or services used by multiple teams Experience building SDKs, API, and automation UIs used by development teams Experience building automation and CI/CD