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Manager, Machine Learning Research - SIML, ISE

Job in Cupertino, Santa Clara County, California, 95014, USA
Listing for: Apple Inc.
Full Time position
Listed on 2025-12-11
Job specializations:
  • Software Development
    AI Engineer, Machine Learning/ ML Engineer
Job Description & How to Apply Below

Manager, Machine Learning Research - SIML, ISE

Cupertino, California, United States Machine Learning and AI

The Human and Object Understanding (HOUr) team at Apple is looking for ML leaders in the space of advanced face analysis. This is an opportunity to join a team that built the fundamental ML technologies behind a number of marquee features spanning Camera, Photos, Accessibility, Apple Wallet, Apple Intelligence, and more. We are looking for world class technology leaders that have the ability to translate ideas to action, and lead a team of experts to innovate, build, deploy and maintain groundbreaking face understanding and perception technologies to enable a variety of new features across the Apple ecosystem, such as:

  • User gaze from RGB images to enable novel interaction experiences:
    Apple Newsroom
  • Face liveness in the RGB domain for anti-spoofing, user authentication and security:
    Apple Newsroom
  • Face analysis for creating exciting new Camera and Photos experiences:
    Apple Support
  • Rich face attribute understanding for enabling personalized and identity preserving image generation, and much more! Apple Newsroom
We are seeking a leader to join our team who can thrive in cross‑functional settings, can provide critical technical expertise and leadership, and be responsible for delivering ML solutions that serve the intended experiences while respecting practical constraints such as memory, latency and power. Description

Candidates for this role must have a proven track record of leadership in applied ML research. The primary responsibilities associated with this position include providing mentorship and technical guidance to a team of ML experts, guiding the team to transform research into impactful solutions in production via extensive multi‑functional collaboration, staying abreast with academic and industry advancements and best practices in ML.

You will be leading an ML team to build the next generation of face analysis technologies such as understanding facial attributes, face liveness and anti‑spoofing, eye tracking and gaze analysis. You will lead the charge in leveraging state‑of‑the‑art techniques to develop highly efficient, real‑time solutions where needed, and/or also leverage pre‑trained large‑scale visual/multimodal foundation models to achieve innovative quality. You will be interacting very closely with a variety of ML leaders, researchers, software engineers, hardware & design teams cross‑functionally in order to build and ship new experiences based on your technologies.

Ensuring quality in the field, with an emphasis on fairness and model robustness would constitute an important part of the role. YOUR PRIMARY RESPONSIBILITIES WILL INCLUDE:

  • Leading an ML team in designing, implementing, and deploying state‑of‑the‑art solutions for advanced face analysis and understanding.
  • Directly interacting with all cross‑functional stakeholders to gather product requirements and translating these into actionable plans for ML research and development.
  • Effectively communicating results and insights gained to partners and senior leaders, providing clear and actionable recommendations.
  • Staying abreast with the latest trends, technologies, and standard methodologies in computer vision, machine learning, and large‑scale foundation models.
  • Actively contributing to ML community at the company by disseminating research ideas and results, enhancing shared infrastructure, and mentoring fellow practitioners.
Minimum Qualifications
  • Master's, or Ph.D. in Computer Science, or Computer Engineering; similarly related fields, or comparable professional experience.
  • Demonstrated technical leadership in industry, and experience in leading ML teams focused on productizing research.
  • Extensive knowledge and experience with large‑scale foundation models including multi‑modal LLMs or vision‑language models, including pre‑training and/or adapting pre‑trained models for downstream perception tasks.
  • Ability to be hands‑on when needed:
    Strong programming skills in Python and C++ and proficiency in toolkits like Pytorch, or equivalent deep learning frameworks.
Preferred Qualifications
  • Strong background in research and innovation,…
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