Video Machine Learning Engineer

Apple • San Diego, CA

2d

About The Position

As a Video Machine Learning Algorithm Engineer on our team, you will be at the forefront of designing, developing, and deploying machine learning solutions that redefine how video is experienced across Apple's ecosystem. You will collaborate with a world-class group of researchers and engineers to tackle challenging problems in video processing and understanding — from crafting novel neural network architectures to optimizing models for on-device performance. Your work will span the full lifecycle of innovation: researching state-of-the-art techniques, prototyping new ideas, training and evaluating models, and shipping production-quality solutions that delight users. If you thrive at the intersection of deep learning research and real-world product impact, this role will give you the platform to do the best work of your career.

Requirements

• BS in Computer Science, Electrical Engineering, Machine Learning, or a related field Strong foundation in deep learning and neural network design, including hands-on experience building, training, and deploying models.
• Proficiency in one or more deep learning frameworks such as PyTorch or TensorFlow.
• Experience with computer vision and/or image and video processing techniques.
• Strong programming skills in Python and/or C/C++, with demonstrated ability to debug and solve complex technical problems.

Nice To Haves

• MS or PhD in Computer Science, Electrical Engineering, Machine Learning, or a related field with a focus on video or visual computing.
• Experience with video codec and compression techniques, including familiarity with standards such as H.264, H.265/HEVC, AV1, or VVC.
• Knowledge of ML-based image and video codecs, including neural compression and learned representations.
• Experience with diffusion models and generative approaches for image and video synthesis or enhancement.
• Familiarity with advanced video quality metrics (e.g., VMAF, LPIPS, DISTS) and perceptual quality evaluation methodologies.
• Experience optimizing and deploying neural networks on edge devices or mobile platforms.
• Published research in top-tier venues (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML) in relevant areas.
• Strong communication and collaboration skills, with the ability to work effectively in cross-functional teams.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees