ISE, SIML - Mobile Deep Learning Performance Engineer
Santa Clara Valley (Cupertino) , California , United States
Machine Learning and AI
Posted: Oct 13, 2020
Weekly Hours: 40
Role Number: 200197573
iPhone is the most popular camera in the world. The precise integration of software and hardware has led to features like Memories and Portrait Mode which deliver experiences that are magical. The Camera & Photos team focuses on user-experience by demonstrating computer vision and image processing through machine learning. Our team works hard on products that ship to millions of people. We are looking for people who want to do the same. System Intelligent and Machine Learning (SIML) is responsible for machine learning solutions for Apple's image and video processing technologies, including features such as face recognition and scene classification in Photos, macOS and iOS system frameworks, and many other internal tools and prototypes under development.
- Strong experience in C++ and Python
- Deep understanding of abstraction and modularity, and performance analysis and tuning
- Ability to master new concepts and technology, rapidly
- Strong dedication to the core values of Apple, ensuring the highest standards of quality, innovation, scientific rigor, and respect for our customers and their privacy
Our team is now hiring software R&D engineers to develop frameworks and tools to accelerate and help reduce the footprint of deep learning applications on iOS and other platforms in the Apple ecosystem. You will help develop software features in C++, Python, and other environments, as well as interfacing and engaging with deep learning research to reduce the computational complexity of the models, while preserving the quality metrics. Prior research experience is not required, but you should be familiar with design solutions that advance the state of the art in any of several fields, such as novel algorithms for optimized deep learning inference and machine learning. Our team combines research and development in a fast-paced environment to produce the products that millions of our customers love to use and rely on every single day.
Education & Experience
B.A./B.S., M.S., or Ph.D. in Computer Science, Mathematics, Physics, or a related field (or equivalent practical experience). We will also consider students still enrolled in school for internship opportunities
- Familiarity with concepts and tools of machine learning and deep learning