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Home›Jobs›Apple›Camera Machine Learning Engineer - Camera Hardware
Apple

About Apple

The personal technology company redefining user experience

🏢 Tech, Hardware👥 1001+ employees📅 Founded 1976📍 Cupertino, CA⭐ 4.2
B2CB2BHardwareSaaSTelecommunicationseCommerce

Key Highlights

  • Market cap of $3 trillion as of 2022
  • Over 1 billion active devices worldwide
  • Comprehensive medical plans including mental healthcare
  • Paid parental leave and gradual return-to-work program

Apple Inc. (NASDAQ: AAPL), headquartered in Cupertino, CA, is the world's most valuable company with a market capitalization of $3 trillion as of 2022. Known for its iconic products such as the iPhone, iPad, and Mac, Apple serves over 1 billion active devices globally. The company has a strong commi...

🎁 Benefits

Apple offers comprehensive medical plans covering physical and mental healthcare, paid parental leave, and a gradual return-to-work program. Employees...

🌟 Culture

Apple's culture emphasizes an obsessive focus on user experience and consumer privacy, setting it apart from competitors. The company promotes inclusi...

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Apple

Camera Machine Learning Engineer - Camera Hardware

Apple • California, United States

Posted 2 months ago🏛️ On-SiteMid-LevelMachine learning engineer📍 San francisco
Apply Now →

Job Description

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.

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

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.

Eeo Content

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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