Machine Learning Research Engineer, Generative AI

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

Machine Learning Research Engineer focused on applying generative AI and ML to create innovative user experiences for hundreds of millions of users across Apple platforms. The role involves the full development cycle from ideation to productization, covering areas like handwriting and text recognition, synthesis, document understanding, and freeform drawing generation, with a focus on computer vision, speech recognition, deep learning, and multimodal LLMs.

What you'd actually do

  1. bringing innovative ideas and applying modern machine learning methods to solve problems that matter
  2. participate in the full development cycle of core technologies, including handwriting and text recognition, handwriting synthesis, document understanding, freeform drawing recognition and generation
  3. applying machine learning and generative AI technologies to create innovative user experiences
  4. help build intelligent features that are reaching hundreds of millions of users across Apple platforms

Skills

Required

  • 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 or multimodal LLMs
  • Experience with image processing, computer vision, speech recognition, or natural language processing
  • Proven track record of programming, debugging, and design skill

Nice to have

  • Detailed knowledge of one or more of the following programming languages: C++, C, Objective-C, or Swift
  • Experience with common ML toolchain such as PyTorch, TensorFlow, or JAX
  • Proficiency with Unix, iOS, or macOS development
  • 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
  • High-quality communication skills and ability to work through ambiguity

What the JD emphasized

  • Industry experience in building product features based on ML including generative models or multimodal LLMs
  • Proven track record of programming, debugging, and design skill

Other signals

  • building intelligent features
  • applying machine learning and generative AI technologies
  • creating innovative user experiences
  • reaching hundreds of millions of users
  • full development cycle of core technologies
  • handwriting and text recognition
  • handwriting synthesis
  • document understanding
  • freeform drawing recognition and generation
  • computer vision
  • speech recognition
  • deep learning
  • multimodal LLMs