ML Engineer - Ads ML Infrastructure

Overview

At Apple, we work every day to create products that enrich people's lives. Our Ad Platforms 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 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 Ad Platforms teams to build and scale the innovative ML systems that deliver highly optimized advertising content to consumers. You will work closely with engineers and data scientists to design, develop, and build platform capabilities that enable Ad Platforms teams to improve and scale our ML features, models, and applications in an Agile environment.

The ML Platform team is responsible for bringing numerous features to advertisers and consumers while supporting scalable modeling and continuous experimentation by all Ad Platforms teams. As a key contributor, you will design and develop secure and scalable back-end systems, building high-performing and elegant systems from the ground up. You will shape architectures to meet unique ad network challenges and build machine learning products that align with Apple s privacy commitments.

You will join a team of world-class machine learning engineers dedicated to reliability, simplicity, and scalability, collaborating with various teams to deliver extraordinary experiences for customers.

• Design and develop secure, scalable back-end systems to support feature delivery for advertisers and consumers.
• Define and refine architectures to meet ad network challenges while upholding privacy commitments.
• Collaborate with engineers and data scientists to build platform capabilities that improve and scale ML features, models, and applications.
• Contribute to a culture of reliability, simplicity, and scalability within a fast-paced team.

• Proven track record of designing and operating large-scale, low-latency ML serving platforms supporting real-time and batch inference.
• Experience with model quantization, tensor parallelism, and inference optimizations (e.g., ONNX Runtime, TensorRT, vLLM); led evaluation and adoption of such technologies.
• Experience with distributed systems (e.g., Ray, high-throughput RPCs) to support scalable inference workloads and hybrid online/offline serving patterns.
• Hands-on experience designing and optimizing low-level GPU kernels to maximize hardware utilization and accelerate deep learning primitives.
• Prior experience in advertising, federated learning, and privacy-preserving ML techniques.
• Recognized as a technical leader and mentor; supports growth through code/design reviews and knowledge sharing.
• Led development of foundational AI/ML platforms and tooling (e.g., Feature Stores, Vector DB) to accelerate productivity and model lifecycle management.
• Experience with performance tuning and troubleshooting.
• Strong emphasis on developer experience; builds abstractions, automation tools, and reusable components for ML workflows.
• Effective written and verbal communication with technical and non-technical teams.
• Results-oriented with the ability to work in a fast-paced, collaborative environment.

• PhD, MS, or BS in computer science or a related field, with 8+ years of experience in machine learning and software engineering.

Base pay ranges from $184,700 to $324,800 and is determined by skills, qualifications, experience, and location. Apple offers additional benefits, including stock programs, comprehensive medical and dental coverage, retirement benefits, products and services discounts, and educational expense reimbursement. Discretionary bonuses may apply where eligible.