Software Engineer, Data & Machine Learning Systems

Apple • Seattle, WA

11h

About The Position

Imagine shaping how millions of people discover content they love on the App
Store, Apple Music, and Apple TV+. Our team is responsible for the intelligence
that powers these deeply personal experiences. We are at a pivotal moment,
defining the next generation of personalization. We build the foundational
capabilities that empower product and research teams to deliver
hyper-personalized experiences while maintaining an uncompromising commitment to
user privacy. We believe that deep personalization shouldn't require
compromising user trust, and we are pioneering the decentralized data systems to
prove it.

This is not a standard Data Engineering or Machine Learning role. We are looking
for a pioneering engineer to join our team. You will build the systems that
securely process, combine, and deliver the critical user and content signals
needed for personalization, spanning from edge devices to cloud backends.
You will engineer high-performance stacks that transform raw data into governed,
discoverable intelligence, ensuring that machine learning models can seamlessly
and securely access the right user and content signals regardless of where that
data physically resides.

Requirements

• BS or MS in Computer Science, Data Engineering, Software Engineering, or a related field.
• Senior-Level Experience: A proven track record of shipping complex, large-scale data engineering, feature serving, or machine learning systems to production.
• Mastery of Big Data & Serving: Expertise in designing distributed data processing systems using technologies like Spark and Flink, and building low-latency, high-throughput data serving layers or Feature Stores.
• Strong Software Engineering: Deep proficiency in Java or Go for building high-performance production backend systems, and Python for model training ecosystems.
• Strategic Data Mindset: Demonstrated experience thinking critically about data architecture, including data ontology, discoverability, and bridging distributed data sources.

Nice To Haves

• Hybrid/Edge Computing: Experience building systems that bridge cloud backend systems with on-device or edge compute environments.
• Embeddings & Vector Search: Familiarity with generating, managing, and serving dense embeddings for retrieval, ranking, and personalization systems.
• Data Governance: Experience building semantic layers, data catalogs, or implementing compliance-by-design in a regulated environment.
• Privacy-Preserving Tech: Passion for privacy and an understanding of data minimization strategies, secure enclaves, or Privacy-Enhancing Technologies (PETs).

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees