SIML - Machine Learning Engineer / Generative AI Engineer, ISE

vor 4 Wochen


Zürich, Schweiz Apple Inc. Vollzeit

Are you interested in creating products that use machine learning and computer vision in novel and interactive ways? Are you looking to apply your expertise to produce transformative features like Live Text and Scribble? Using generative models to build highly visible products that are getting into the hands of hundreds of millions of users? We are an applied machine learning team distributed between Zurich in Switzerland and Cupertino in California, searching for a motivated research lead engineer to help develop the future of ML models to power products around text and freeform drawing recognition and generation. We work closely with diverse teams throughout Apple.

Description

As a member of the team, you will be responsible for bringing innovative ideas to our next generation of products, applying modern machine learning methods to solve problems that matter. The work spans the entire product life cycle from project inception to shipping models on billions of devices. We are seeking an engineer who will be responsible for prototyping new features as well as contributing to the overall design and development of existing components. The ideal candidate should have experience in computer vision, speech recognition, deep learning, and/or other applications of machine learning systems.

Minimum Qualifications

  • PhD or MSc in Computer Science, Computer Engineering or a closely related field.
  • Industry experience in building product features based on ML including generative models.
  • Experience with image processing, computer vision, speech recognition, or natural language processing.
  • Strong programming, debugging, and design skills.

Preferred Qualifications

  • Excellent problem solving, critical thinking, and interpersonal skills.
  • Ability to produce creative and innovative solutions to challenging problems.
  • Enthusiastic about building end-to-end experiences using machine learning.
  • Experience building deep learning toolkits with modern tools.
  • Detailed knowledge of one or more of the following programming languages: C++, C, Objective-C, or Swift.
  • Detailed knowledge of a common ML toolchain such as PyTorch, Tensorflow, or JAX.
  • Proficiency with Unix, iOS, or macOS development.
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