Machine Learning Engineer, Video Engineering

Role Overview

Help define the next generation of photo and video experiences at Apple. The Video Engineering group develops key image and video technologies that contribute to experiences across many Apple products and services. As a Machine Learning Engineer, you'll be developing breakthrough ML models that power spatial media features, including 3D photos, immersive video, and scene reconstruction, reaching hundreds of millions of users. As a member of a fast-paced team, you will have the unique and exciting opportunity to shape upcoming products at the frontier of generative AI, computer vision, and 3D understanding, with a strong emphasis on taking ideas from research to production.

Responsibilities

This role requires an independent, self-motivated, and creative engineer with deep expertise in machine learning, coupled with a strong understanding of 3D computer vision and computer graphics. Your primary focus will be applying cutting-edge machine learning techniques to complex 3D visual challenges to create customer impact across current and future Apple products.

Requirements & Qualifications

Minimum Qualifications

Bachelor's degree in Computer Science, Electrical/Computer Engineering, or a related field.

10+ years of experience developing and shipping machine learning models, with a focus on computer vision or generative AI. Expert-level proficiency in Python and PyTorch or equivalent ML frameworks. Strong experience with diffusion models for image synthesis, video generation, 3D generation, or related domains.

Solid understanding of 3D computer vision including depth estimation, multi-view geometry, 3D reconstruction, novel view synthesis, or neural scene representations.

Working knowledge of 3D computer graphics concepts such as rendering, camera models, scene representations, and coordinate systems. Working knowledge of C++ for performance-critical components. Ability to leverage AI coding assistants and LLM-based tools to accelerate development, prototyping, and problem-solving workflows.

Preferred Qualifications

MS or PhD in Computer Science, Machine Learning, Computer Vision, or a related field. Publications in top-tier ML or vision venues. Experience with video diffusion models, 3D Gaussian Splatting, neural radiance fields, or differentiable rendering. Experience with distributed training at scale. Familiarity with on-device ML deployment. Track record of shipping ML-powered features in consumer products. Good written and oral interpersonal skills.

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 $184,700 and $324,800, 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 Engineer, Video Engineering↗.

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