Computer Vision and Machine Learning Engineer, Creativity Apps

Apple Apple · Big Tech · Cupertino, CA · Software and Services

This role focuses on building and delivering state-of-the-art machine learning models for creative editing tools within Apple's consumer products. Responsibilities include data collection, model architecture design, training custom models, and partnering with cross-functional teams to integrate these features from concept to delivery. The ideal candidate has significant industry experience in computer vision and machine learning, with hands-on experience in building, training, evaluating, and deploying various model types, particularly vision models.

What you'd actually do

  1. Build state-of-the-art machine learning models to power application features.
  2. Collect model training data, design model architectures, and train custom models suited for application features.
  3. Partner with cross-functional teams to design and implement end-to-end machine learning enabled features to power the next-generation tools for creators.
  4. Drive application features from concept, model design, development and all the way to delivery.

Skills

Required

  • MS Computer Science, Machine Learning or related field
  • 2+ years of significant industry experience
  • theory and practice of computer vision, machine learning and deep learning techniques
  • building, training, evaluating, and deploying transformer based vision models, Generative Adversarial Network based models, or related methods
  • Strong programming skills in Python and/or C++
  • one of the deep learning toolkits such as PyTorch, JAX, or Tensorflow

Nice to have

  • PhD in Computer Science, Machine Learning or related field
  • Experience delivering high quality software at scale
  • modern camera ISP and digital image processing algorithms and models
  • optimizing models and algorithms that run efficiently on resource constrained platforms
  • Core ML, Swift, and iOS/macOS machine learning development
  • Knowledge and keen interest in learning the art and science of photography

What the JD emphasized

  • delivering products
  • delivering products
  • delivering products

Other signals

  • building state-of-the-art machine learning models
  • train custom models
  • deliver end-to-end machine learning enabled features
  • deliver products using state-of-the-art computer vision and machine learning technologies
  • delivering products in Computer Vision, Computational Photography, Generative AI, Machine Learning
  • building, training, evaluating, and deploying transformer based vision models, Generative Adversarial Network based models