Embedded Systems Engineer Jobs at Apple with Visa Sponsorship

The Applied Sensing & Health team develops software that powers the next generation of fitness, safety, and health experiences. We transform complex, multi-modal sensor data from the iPhone, Apple Watch, and AirPods into meaningful and elegant insights about our users' health, wellbeing, and safety. By combining advanced machine learning—including the integration and tuning of foundation models—with domain knowledge and scientific research, we have delivered impactful features like Cardio Fitness, Journaling Suggestions, Fall and Crash Detection, and Walking Steadiness. As a dynamic and highly multi-disciplinary team working at the intersection of research and product development, you will have the opportunity to build the next generation of sensing-based features that will motivate, inform, and inspire millions of Apple's customers every single day.

Description

You will help ship high-quality, interactive Health, Fitness, and Safety features that impact millions of Apple Watch, iPhone, and AirPods users. You have a deep sense of ownership and feel a personal stake in the products you ship. You are comfortable navigating ambiguity in early-stage development, demonstrate initiative, and work well under tight deadlines. You build strong, collaborative relationships with others and are dedicated to a culture of continuous improvement for yourself, your team, and our products.

Responsibilities

In this role, you will implement and ship interactive software features and algorithms that impact millions of users on a daily basis. You will be responsible for optimizing software implementations for power, memory, and performance, especially within the constraints of embedded, low-power systems. Operating at the intersection of software, data engineering, and machine learning, you will collaborate closely with scientists, engineers, QA, and project managers throughout the software lifecycle.

Minimum Qualifications

Bachelor's in Computer Science, EECS, or equivalent experience.

Developed C/C++, ObjC or Swift code for a shipping product or a peer reviewed environment.

Background in developing, debugging and optimizing algorithms for low-power embedded systems.

Preferred Qualifications

Masters or PhD in Computer Science, EECS, machine-learning or equivalent experience.

2+ years of technical experience in an industry setting.

Background in developing deep learning, foundation, and/or generative AI models for multiple data modalities (time series, images, language, etc.).

Experience collaborating in small teams.

Excellent interpersonal skills and communication (written and verbal).

Pay & Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $171,600 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses—including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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.