Job description

You have a demonstrated track record of identifying the right problems, taking calculated risks, and shipping at scale. In this role, you will lead end-to-end incubations from early ideation to deployment, applying state-of-the-art ML research, algorithmic innovation, and agentic systems to challenges with both immediate and long-term company-wide impact. You bring deep intellectual curiosity, the ability to operate at the frontier of applied research, and the excellent communication skills to align executives and cross-functional partners alike. When your work breaks new ground, you will have the opportunity to publish your findings and engage with the broader academic community all while driving real-world impact at Apple's global scale. 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 industry experience working within 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 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

Requirements

Must-haves

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 industry experience working within 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
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

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlmachine learningai

Platform: apple
Effort: medium