at Apple
Location
Cupertino, United States of America
Compensation
$181k–$318k USD
Type
full time
Posted
3 months ago
Market range · company + function + seniority
p25 · target · p75 · n=652
Posted $318k · in the market band
Posting health
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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.
Bachelor’s in Computer Science, Machine Learning, Electrical Engineering, or a related field — or equivalent practical experience.
Strong software engineering fundamentals in an object-orient programming language, with emphasis on writing production-grade, testable, and maintainable code.
Experience with Systems Programming (frameworks/libraries/daemons).
7+ years of industry experience in machine learning engineering, with at least 2 years focused on on-device/edge ML deployment.
Strong proficiency in ML frameworks and tool chain such as PyTorch, TensorFlow, Core ML, Foundation Models Framework and MLX.
Proven track record of shipping ML models into production at scale on mobile or embedded platforms.
Master’s, or PhD in Computer Science, Machine Learning, Electrical Engineering, or a related field — or equivalent practical experience.
Familiarity with Swift, and Objective-C.
Experience building and operating end-to-end ML pipelines for on-device models — including training, evaluation, conversion, validation, A/B testing, and OTA model delivery.
Familiarity with federated learning, differential privacy, and on-device training/fine-tuning paradigms.
Apple Maps and the thousands of applications it empowers are being used by millions every single day! As a fundamental tool for human activity, Maps technology is evolving and new techniques are emerging.
We are 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. You will partner with a variety of subject experts across the company to build intelligent features and personalized maps experiences. This role involves collaborating with various partners, from engineers to designers, to architect the best overall system.
If you are excited about delivering intelligent, responsive, and personalized experiences to millions of users, we invite you to apply for the job and join us!
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant
At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
Learn about accessibility in Apple’s workplace
Learn about reasonable accommodations for job applicants
Apple accepts applications to this posting on an ongoing basis.
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