Machine Learning and AI
The work is innovative.
The experience is magic.
The people working here in machine learning and AI are building amazing experiences into every Apple product, allowing millions to do what they never imagined. Because Apple fully integrates hardware and software across every device, these researchers and engineers collaborate more effectively to improve the user experience while protecting user data. Come and make an impact with the products you create and the research you publish.
Any emoji can make people smile, but it takes talented people to make an Animoji smile — and Cecile and her colleagues make sure those expressions are mirrored instantaneously. As an engineering manager at Apple, she’s part of a team that’s responsible for developing the software layers that enable hardware acceleration for neural networks on Apple platforms, delivering real-time performance for a variety of applications. Their innovative approach allows on-device execution, providing better performance and power efficiency for our customers while preserving their data privacy. Cecile attributes these exceptional customer experiences to some inspiring collaboration among people from different backgrounds with different perspectives. “Apple attracts a diverse array of highly skilled engineers, so every time we come together to do something cool, we get this inspiring sweet spot of greatness.”
Find a team and begin your own story here.
Machine Learning Infrastructure
Build the rock-solid foundation for some of Apple’s most innovative products. As part of this team, you’ll connect the world’s best researchers with the world’s best computing, storage and analytics tools to take on the most challenging problems in machine learning. And this is Apple, so your team will innovate across the entire stack: hardware, software, algorithms — it’s all here. Areas of work include Back-End Engineering, Data Science, Platform Engineering and Systems Engineering.
Find available Machine Learning Infrastructure roles
Deep Learning and Reinforcement Learning
Join a team of researchers and engineers with a proven track record in a variety of machine learning methods: supervised and unsupervised learning, generative models, temporal learning, multi-modal input streams, deep reinforcement learning, inverse reinforcement learning, decision theory and game theory. This team dives deep into deep learning and AI research to help solve real-world, large-scale problems. Areas of work include Deep Learning, Reinforcement Learning and Research.
Find available Deep Learning and Reinforcement Learning roles
Natural Language Processing and Speech Technologies
This group is a collective of hands-on research scientists from a wide variety of fields related to natural language processing. Join them to work with natural language understanding, machine translation, named entity recognition, question answering, topic segmentation and automatic speech recognition. This team’s research typically relies on very large quantities of data and innovative methods in deep learning to tackle user challenges around the world — in languages from around the world. Areas of work include Natural Language Engineering, Language Modeling, Text-to-Speech Software Engineering, Speech Frameworks Engineering, Data Science and Research.
Find available Natural Language Processing and Speech Technologies roles
Giulia has been at Apple since the early ’90s. “We were working on machine learning before it was cool,” she says. Today, Giulia leads a natural language processing team, teaching machines to recognise patterns such as numbers, images or words, including over 30,000 handwritten Chinese characters. Although she eagerly follows all the latest academic research, Giulia says collaborating with her team and other groups at Apple also helps her stay at the forefront of her field. “I love the intellectual challenges, but what I love most is turning that thinking into real innovation — a little bit of magic experienced by millions of people around the world.”
Computer Vision
Come and solve the most challenging problems in computer vision and perception. Be part of a multidisciplinary team that designs algorithms to analyse and fuse complex sensor data streams. This team works on everything from low-level image processing algorithms to deep neural network approaches for object detection, always mindful of the balance between algorithm correctness and computational performance. Areas of work include Computer Vision, Data Science and Deep Learning.
Find available Computer Vision roles
Applied Research
Transform groundbreaking ideas into revolutionary features. You’ll take part in core and applied machine learning research focused on both algorithm development and integration. As a software R&D engineer, you’ll develop cutting-edge machine learning algorithms to enable current and future Apple products and services in fields that include health, accessibility and privacy. Areas of work include Machine Learning Platform Engineering, Systems Engineering, Data Science and Applied Science.
