Aiml - Research Scientist, AI Interpretability & Visualization

Apple Apple · Big Tech · Cambridge, MA +2 · Machine Learning and AI

Research Scientist focused on AI interpretability and visualization, developing tools and strategies to make AI systems more understandable, transparent, and safe. The role involves defining research directions, implementing new tools, investigating AI algorithms, and contributing to projects that ship on Apple devices.

What you'd actually do

  1. Define and implement research directions at the forefront of interpretable machine learning
  2. Design and implement new tools and visualizations to make designing, building, and deploying machine-learning based products faster and easier
  3. Investigate innovative machine learning, and artificial intelligence algorithms
  4. Contribute to a variety of projects around Apple, and transfer your ideas into solutions for some of the most ambitious technical problems in the next generation of Apple products

Skills

Required

  • PhD or MS in Computer Science, Machine Learning, or related field or equivalent experience
  • Proficiency with modern AI technologies and building interactive data visualizations
  • Experience shipping products that use machine learning or tools for machine learning interpretability
  • Substantial contributions to research or practitioner communities, such as by publishing papers at top-conferences or contributing to open source projects
  • Proven history of turning ideas into actionable tools, guidelines, or products
  • Excellent verbal and written communication and presentation skills

Nice to have

  • Strong web-development background

What the JD emphasized

  • shipping products that use machine learning or tools for machine learning interpretability
  • Substantial contributions to research or practitioner communities, such as by publishing papers at top-conferences or contributing to open source projects
  • Proven history of turning ideas into actionable tools, guidelines, or products

Other signals

  • interpretability
  • visualization
  • evaluation
  • deployment