Machine Learning Research Engineer

Role Overview

The Human and Object Understanding team (HOUr) in the Intelligent System Experience (ISE) organization is looking for Research Engineers with a strong foundation in Machine Learning and Computer Vision to develop the next generation of multi-modal Human Sensing technologies. You will be part of a fast-paced, impact-driven Applied Research organization building foundation models for facial and full-body perception and working on cutting-edge machine learning that is at the heart of the most loved features on Apple platforms including Apple Intelligence, Camera, Photos, Visual Intelligence, etc.

Responsibilities

As a Machine Learning Research Engineer, you will be responsible for designing and developing cutting-edge AI/ML models for Human Sensing, with a focus on building robust cross-domain identity recognition systems. Multi-modal Human Sensing is a foundational capability that powers intelligent experiences based on key human traits such as identity, expression, clothing, action, gesture, gaze and human-object interaction. Major Apple Intelligence experiences such as personalized Natural Language Search, Memories Creation, as well as personalized Image Generation are powered by our ability to learn robust representations of visual human traits. Efficient real-time visual human sensing powers flagship Photography experiences such as Cinematic mode and Photographic Styles, communication experiences such as Center Stage, and paves the way for more natural human-device interactions, e.g., with the DockKit framework.

Requirements & Qualifications

Minimum Qualifications

Master's or Ph.D. in Computer Science, Computer Engineering, or related fields, or equivalent professional experience in Computer Vision (CV) and Machine Learning (ML) research and development.

Proven track record of training, fine-tuning and evaluating deep learning models for vision tasks using modern ML architectures.

Background in research and innovation, demonstrated through publications in top-tier journals or conferences, patents, or impactful software developments. Proficient in Python, PyTorch or equivalent deep learning frameworks.

Preferred Qualifications

Expert-level knowledge of state-of-the-art methods in face recognition or other facial analysis and biometric systems.

Hands-on experience training and scaling multi-modal large language models (LLMs) or large-scale vision-language models (VLMs)

Experience with on-device ML, model optimization (knowledge distillation, quantization, pruning), or production-grade ML pipelines.

Compensation & Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $142,300 and $263,300, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Application Instructions

Apply directly on Apple Jobs at Machine Learning Research Engineer↗.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant