Machine Learning Engineer - Camera Algorithms

Cupertino,California,United States

Hardware

Are you passionate about developing outstanding camera technologies that enrich the lives of billions of people? Apple’s Camera Algorithms Team builds foundational image and video capture, processing, and rendering algorithms that impact every photo and video on all Apple products. We’re seeking machine learning engineers who share our vision and passion for pushing the boundaries of what’s possible on every Apple device. As part of the team, you will work on core camera and low-level vision technologies, using Apple’s industry leading real-time neural inference processor (Apple Neural Engine) and powerful custom image signal processing engine. You will have the opportunity to showcase your machine learning skills and expertise to help redefine Apple's cameras.

Description

Your primary responsibilities will include developing machine learning technologies, implementing, optimizing, and integrating them into our products. This will entail close collaboration with various functional teams across Apple. You will collaborate closely with product teams to define a problem, work alongside HW/SW/FW teams to prototype, integrate, and optimize algorithms tailored to the hardware capabilities, and you also will engage with the silicon team to do low-level neural network optimization. In this position, you will fully experience Apple’s core culture: thinking differently and pushing the boundaries of technology.

Minimum Qualifications

• BS and a minimum of 3 years relevant industry experience

• Demonstrated ability in developing machine learning algorithms for computational photography/computer vision and image processing problems

• Proficiency in using ML toolkits, e.g., PyTorch

• Strong programming skills in Python, or C/C+ Key Qualifications

Preferred Qualifications

• Proven track record in machine learning based image and video processing, demonstrated through either relevant industry experiences or publications in top-tier conferences (CVPR, ICCV, ECCV, SIGGRAPH, etc)

• Experiences in image restoration (de-noising, super resolution, enhancement, etc)

• Skilled in communication, problem solving, critical thinking

• Understanding camera sensor and ISP algorithm is a plus

• Consistent track record in transitioning technology from prototype to final product is a plus

• ML depth in generative AI is a plus

Education & Experience

Additional Requirements

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 $143,100 and $264,200, 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.Learn more (https://www.apple.com/careers/us/benefits.html) about Apple Benefits.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 take affirmative action to ensure 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. (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf)

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