Apple Maps Client is looking for a Staff Machine Learning Engineer to drive the design, development, and deployment of machine learning models optimized for on-device training and inference. Partnering with the Apple Neural Engine team to profile model performance, identify bottlenecks, and push the limits of what's possible on-device. Crafting technical design documents for new ML features is a core part of this role- outlining model architecture choices, performance targets, and deployment strategies. Your work includes building integration code that connects ML models with platform frameworks and APIs. You will lead cross-functional team projects. Beyond individual contributions, you will shape how the team approaches on-device ML. You will establish evaluation frameworks, define quality benchmarks, and write architecture documents that guide the team's direction. You will review code, mentor engineers, and help build a team culture rooted in technical rigor and collaboration.

Architect and deliver on-device ML solutions that meet strict latency, memory, power, and accuracy requirements across Apple platforms.

Partner with Services teams on model delivery and update mechanisms( OTA model updates, staged rollouts) and define hybrid inference strategies (on-device vs. server-side).

Collaborate cross-functionally with services, platform, and design teams to influence roadmaps, framework capabilities, and user experiences.

Mentor and grow junior and mid-level ML engineers, fostering a culture of technical excellence, curiosity, and inclusive collaboration.

Champion privacy by design — ensuring ML systems uphold Apple's commitment to user privacy through on-device processing, differential privacy, and minimal data collection.