Principal Research Scientist, Siri Innovation Studio

Apple Apple · Big Tech · Seattle, WA +2 · Machine Learning and AI

Principal Research Scientist for Siri Innovation Studio at Apple, focusing on incubating and deploying next-generation AI features for Apple Intelligence. The role involves leading end-to-end ML research and development, from ideation to shipping at scale, with a strong emphasis on applied ML, agentic systems, and user-centered design for a wide range of Apple products. Requires a strong publication record and experience with ML model lifecycles.

What you'd actually do

  1. Lead end-to-end incubations with full technical ownership from ideation and prototyping
  2. Drive advances in applied ML research and development to address strategic priorities across the company
  3. Co-invent novel ML modeling approaches and architectures that unlock new product capabilities
  4. Raise the bar for technical excellence within the team through mentorship, collaboration, and example
  5. Partner with teams across software, hardware, and design to shape product direction, define technical strategy, and deliver scalable ML technologies that delight users

Skills

Required

  • MSc or PhD in Computer Science, Machine Learning, or related field; or equivalent track record of incubating and shipping ML features, platforms, and/or products
  • 5+ years of experience leading an ML team
  • Deep understanding of the ML model lifecycle for large-scale systems
  • Demonstrated expertise in ML with a publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, KDD, ACL, ICASSP, InterSpeech)
  • Proficient modeling skills; deep familiarity with toolkits such as JAX, PyTorch, and/or Tensorflow

Nice to have

  • Demonstrated ability to influence high-level architecture decisions and advocate for novel research directions with product and executive leadership
  • Exceptional communication and interpersonal skills, able to translate complex technical work for a broad audience
  • Experience working across hardware, software, and design partnerships to bring ML capabilities to production
  • Passion for building AI that is both technically rigorous and meaningfully human

What the JD emphasized

  • shipping at scale
  • ML model lifecycle for large-scale systems
  • publication record

Other signals

  • next-generation of Apple Intelligence
  • personal context understanding
  • on-screen awareness
  • shipping technology that is centered around users
  • incubating and deploying innovative technologies and features
  • unlock new capabilities for Siri
  • agentic assistance
  • end-to-end incubations from early ideation to deployment
  • applied ML research
  • algorithmic innovation
  • agentic systems
  • shipping at scale
  • ML model lifecycle for large-scale systems
  • publication record in relevant conferences
  • JAX, PyTorch, and/or Tensorflow