Machine Learning Engineer

New York City, New York, United States Machine Learning and AI

At Apple, we work every day to create products that enrich people’s lives. Apple Ads 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 Search Ads, App Store, and Apple News. Our platforms are highly‑performant, deployed at scale, and setting new standards for enabling effective advertising while protecting user privacy.

The Machine Learning Platform team’s mission is to empower teams at Apple Ads 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 an Agile environment? You will work closely with engineers and data scientists to design, develop, and build world‑class platform capabilities that will enable Apple Ads teams to improve and scale our ML features, models, and applications.

The ML Platform team is responsible for bringing numerous features to advertisers and consumers while simultaneously supporting scalable modeling and continuous experimentation by all Apple 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 machine learning systems from the ground up, in close partnerships with various teams.

You will also possess keen judgment in selecting technologies and building the right solution for the interesting challenges we get to tackle here. You will have the opportunity to define and refine architectures to meet the unique ad network challenges we must solve. 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!

• 10+ years of experience applying ML at scale in ads, recommender systems, content ranking, or related domains.
• Strong expertise in deep learning architectures (Transformers, LLMs, DNNs) and training frameworks (Tensor Flow, PyTorch).
• Experience with privacy‑preserving ML (federated learning, differential privacy, homomorphic encryption, secure multiparty computation) is preferred.
• Familiarity with machine learning libraries and frameworks.
• Experience writing machine learning applications and mission‑critical code for production machine learning systems.
• Experience building and scaling cloud‑based architectures.
• Experience building AI/ML tooling and/or infrastructure.
• Experience working on distributed systems where scalability and performance are critical.
• Prior experience in model optimization is a huge plus.
• Understanding of software engineering principles for maintainable code development.
• Ability to communicate effectively, both written and verbal, with technical and non‑technical multi‑functional teams.
• Ability to set technical direction and deliver business impact.
• Results oriented with a desire to work in a fast‑paced and collaborative work environment.
• Prior experience in advertising industry is a huge plus.

• Education & Experience
• PhD/MS/BS in Computer Science or related field with 9+ years of industry experience in building large‑scale distributed software systems.

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation…