Camera Machine Learning Engineer

Are you a passionate Machine Learning Engineer with a deep love for photography? Join Apple's Camera Hardware Engineering team and help us redefine the camera experience for millions of users worldwide. As a key player in our innovative team, you will collaborate closely with hardware, software, and image processing specialists to develop cutting-edge camera technologies.

Description

As a Machine Learning Engineer in the Camera Hardware Engineering group you will be responsible for all research, design, development, test, and qualification of camera hardware for Apple products. This team is seeking an experienced Machine Learning Engineer with a background in Camera and image sensor technologies. You will bring your expertise to the team and be responsible for ongoing design, evaluation, benchmarking and characterization of Apple camera products.

Responsibilities

• ML Algorithms: Research, design, and implement machine learning algorithms for various camera tasks, including image and video processing, computational photography, and scene understanding.
• Data-Driven Development: Collaborate with data collection teams to curate large-scale image and video datasets and perform data analysis and preprocessing to train and validate your ML models effectively.
• Prototyping and Evaluation: Develop prototypes of ML algorithms and evaluate their performance through rigorous testing and user feedback. Your insights will drive continuous improvement.

Minimum Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, Physics, Optics, or a related field
• Experience with Python programming and deep learning frameworks like PyTorch
• Experience with machine learning and computer vision principles, and algorithms.
• Experience with camera and/or image sensor technologies.

Preferred Qualifications

• MS or Ph.D. in Machine Learning, EE, CS, Physics, Optics, or equivalent and 3+ years of experience in machine learning research or relevant industry experience
• Experience with applying deep learning to various computer vision tasks, such as: Object recognition, Image segmentation, Inpainting, and Anomaly detection
• Experience in applying generative AI and reinforcement learning techniques to enhance hardware design processes.
• Experience with using advanced ML methods to optimize system architectures and improve image quality in the hardware design domain.
• Experience with image quality metrics and evaluation methodology
• Experience with camera components, functions, and the camera ISP pipeline
• Experience with megapixel CMOS image sensor technology, lens selection, and qualification

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 $147,400 and $272,100, 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. Learn more 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 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 .

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