Apple

About Apple

The personal technology company redefining user experience

🏢 Tech, Hardware👥 1001+ employees📅 Founded 1976📍 Cupertino, CA4.2
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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...

Apple

Machine Learning Engineer – Computer Vision & Data Systems

AppleSunnyvale, California, United States

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Job Description

At Apple, we are dedicated to creating technologies that enrich people's lives. Our teams develop products and experiences that empower millions of users globally, by combining world-class engineering with a deep commitment to innovation, quality, and privacy. We are seeking a Machine Learning Engineer with strong expertise in computer vision and large-scale data processing. In this role, you will contribute to the development of next-generation real-time sensing and data intelligence systems by designing algorithms, building scalable data pipelines, and collaborating with multi-functional teams to deliver high-impact, production-quality solutions. As a Machine Learning Engineer, you will: - Design, build, and maintain large-scale data processing workflows, ensuring efficiency, scalability, and reliability across diverse data sources and modalities. - Develop and optimize computer vision models that power core product experiences, including areas such as image understanding, multi-view geometry, 3D reconstruction, and visual recognition. - Partner closely with engineering, research, and data teams to translate product requirements into technical solutions. This includes prototyping models, running large-scale experiments, improving data quality, and ensuring seamless integration of algorithms into production systems. - Explore emerging areas such as LLM-based agents, retrieval-augmented systems, and tool-oriented reasoning to improve internal workflows or data operations.

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