ML Research Engineer, HOUr - ISE

Apple • Cupertino, CA

12h

About The Position

The Human and Object Understanding (HOUr) team in Apple’s Intelligent System Experience (ISE) organization is seeking ML research engineers focused on advanced face understanding and analysis. The team has developed machine-learning technologies used in products and features including visual user identification for Apple HomeView, visual age estimation for child safety on Apple platforms, gaze understanding in Camera and Photos and Accessibility, and liveness assessment for IDs in Apple Wallet.

The role applies machine-learning research to use-case-specific and feature-enabling technologies in visual identity, facial attributes, face liveness and anti-spoofing, eye tracking, and gaze analysis. Engineers develop efficient, real-time solutions where needed and may adapt large-scale pretrained visual or multimodal foundation models to achieve high quality for downstream use cases. The role works closely with feature and product teams and collaborates with ML leaders, researchers, software engineers, and hardware and design teams to build and ship new experiences. Ensuring product quality in the field, with attention to fairness and model robustness, is an important part of the work.

Requirements

• Master’s or Ph.D. in Computer Science, Computer Engineering, or a related field, or comparable professional experience.
• Extensive knowledge and experience leveraging large-scale foundation models, including multimodal LLMs or vision-language models, and adapting or distilling pretrained models for downstream perception tasks.
• Strong programming skills in Python.
• Proficiency with PyTorch or an equivalent deep-learning framework.
• Proficiency in using AI coding and productivity tools to accelerate experimentation and model-training iterations.
• Proven track record of domain expertise and technical leadership in applied ML research.

Nice To Haves

• Research and innovation background demonstrated through publications in top-tier journals or conferences, patents, or impactful industry experience.
• Experience transitioning prototypes into shipping products.
• Familiarity with developing algorithms that run efficiently on resource-constrained platforms.
• Excellent written and verbal communication skills, comfort presenting research to large audiences, and ability to work in multifunctional teams.

Responsibilities

• Develop applied machine-learning technologies for visual identity, facial attributes, face liveness and anti-spoofing, eye tracking, and gaze analysis.
• Leverage state-of-the-art techniques to develop efficient, real-time solutions where needed.
• Adapt or use pretrained large-scale visual and multimodal foundation models for downstream use cases.
• Partner with feature and product teams to build use-case-specific and feature-enabling technologies.
• Collaborate with ML leaders, researchers, software engineers, and hardware and design teams to build and ship new experiences.
• Help ensure quality in the field, with an emphasis on fairness and model robustness.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior