Senior Backend Systems Engineer, Sensing & Connectivity

Apple • San Diego, CA

4d

About The Position

Build the backend systems that power location intelligence for billions of people. Craft the next generation of location-aware experiences by architecting systems that seamlessly connect people's digital and physical lives — at a scale few engineers ever get to work with. Are you passionate about solving hard problems in clever ways? Do you love digging into data and proposing bold ideas, not just implementing them? Do you want your work to have real impact — from someone's daily commute to a life-critical emergency? If so, we might just be the team for you. Here at Apple, we build devices and services that enrich our customers' lives. In the location technologies group, we power navigation, emergency response, fitness, and a rapidly expanding set of indoor and outdoor services across new and existing hardware — spanning the full stack from raw sensors to the application layer. We reach more than a billion people every day, and what we do makes a difference. Join our team, and we'll help you do the best work of your life. If you join our team, you'll architect and build backend systems that process crowdsourced sensor data from hundreds of millions of devices, fueling algorithms that solve problems from everyday navigation to life-critical emergencies. You'll propose ideas, crunch data, leverage modern AI tools, and ship systems that run under demanding real-world efficiency requirements at global scale. If you join our team, you'll bring machine learning expertise and strong software engineering craft to bear on some of the hardest sensor data problems in the world. You'll design, build, and maintain high-quality, production-grade software systems — writing well-architected, testable, and performant code that others on your team rely on every day. You'll design and build signal processing pipelines and data infrastructure that ingest and interpret crowdsourced sensor data from hundreds of millions of devices — and apply ML to extract intelligence from those streams at scale. You'll own the full ML lifecycle: from problem formulation and feature engineering on raw sensor data, through model development and experimentation, to building the infrastructure that takes models reliably into production. You'll solve problems ranging from everyday navigation to life-critical emergencies, propose bold ideas, crunch data, leverage modern AI tools, and ship systems that run under demanding real-world efficiency requirements at global scale.

Requirements

• Proficient in Java or equivalent backend languages such as Scala
• Strong foundation in object-oriented design, distributed systems, and real-time software architecture
• Master's or PhD in Computer Science or related field, or a Bachelor's degree with proven experience architecting real production systems at scale
• Demonstrated experience architecting and operating high-scale production backend systems
• Experience with crowdsourced, sensor, or telemetry data systems
• Comfortable implementing complex mathematical or statistical algorithms
• Familiarity with AI/ML tools applied to accelerate development and analysis
• Familiar with Linux-based development environments
• Strong communication skills — you can explain complex systems clearly to any audience
• Curious and energized by problems that do not have obvious solutions yet

Responsibilities

• Architect and build backend systems that process crowdsourced sensor data from hundreds of millions of devices.
• Fuel algorithms that solve problems from everyday navigation to life-critical emergencies.
• Propose ideas, crunch data, leverage modern AI tools, and ship systems that run under demanding real-world efficiency requirements at global scale.
• Bring machine learning expertise and strong software engineering craft to bear on some of the hardest sensor data problems in the world.
• Design, build, and maintain high-quality, production-grade software systems — writing well-architected, testable, and performant code.
• Design and build signal processing pipelines and data infrastructure that ingest and interpret crowdsourced sensor data from hundreds of millions of devices.
• Apply ML to extract intelligence from sensor data streams at scale.
• Own the full ML lifecycle: from problem formulation and feature engineering on raw sensor data, through model development and experimentation, to building the infrastructure that takes models reliably into production.
• Solve problems ranging from everyday navigation to life-critical emergencies.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior