Computer Vision & Machine Learning Engineer – Body Understanding (m/f/d) Full-time

Summary
Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there’s no telling what you could accomplish. Multifaceted, amazing people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same passion for innovation that goes into our products also applies to our practices strengthening our commitment to leave the world better than we found it. Join us to help deliver the next groundbreaking Apple product! Do you love working on challenges that no one has solved yet? At Apple, we are pushing the boundary of what is possible to improve the lives of our customers.

Are you eager to work at the intersection of Computer Vision and Deep Learning, on projects that turn technical innovation into Apple products which touch the lives of millions of people? Then join the Munich Vision Lab as a CV/ML Engineer.

Our team has brought to live the Persona technology that powers FaceTime on Apple Vision Pro. Help us develop groundbreaking technology in real-time image-based pose and shape recovery for more human body understanding use cases.

We are looking for candidates with outstanding technical expertise, ideally with a track record in algorithm development for image-based deep learning, multimodal foundation models, multi-view geometry, human motion capture, or a highly related discipline. You should be able to quickly prototype different algorithm solutions, but also to elevate them to production standard. Join us for the rare opportunity to work on computer-vision-driven products that go beyond the state of the art and that delight and inspire millions of Apple’s customers every single day.

Description
In this role as a CV/ML engineer, you will be developing image-based algorithms for body understanding. The scope of our team encompasses the entire project cycle, from the initial cross-functional definition to prototype development, quality evaluation, and product integration. As the ML algorithms team, we are responsible to source our training data by specifying requirements and ensuring their implementation in both real and synthetic data campaigns. Responsibilities include data handling, including capturing, processing and managing large datasets, data cleaning, transformation, and augmentation, as well as identifying the ideal algorithm and model architecture for a particular use case and hardware configuration.