San Diego, California, United States · $139,500-258,100/yr
Machine Learning Video Algorithm Engineer
Apply NowThe codec deep video processing team develops machine learning algorithms to power Apple technologies with the best user visual experience. In this role, you will work closely with company-wide multiple teams and in multiple projects, from data curation to model development, in a large-scale, to help deliver new features for Apple products and bring high impact to millions of users. Join us as a Machine Learning Engineer and build the next-generation video processing features. You will play the key role from data to feature development. In this role, you will identify and develop machine leaning solutions and work closely with multiple teams to optimize and productize those features.
Key Responsibilities
• Design and develop data curation pipeline for pre-training and post-training. • Design and implement deep learning algorithms for video related tasks. • Design test suite and evaluation pipeline for validation and testing. • Optimize models and algorithms for performance, including latency, memory, and computational efficiency. • Integrate solutions into end-to-end video processing pipelines.
Minimum Requirements
• BS and a minimum of 3 years relevant industry experience. • Experience evaluating supervised, unsupervised, and deep learning models. • Proficiency in Python and libraries such as NumPy, pandas, scikit-learn, PyTorch, or TensorFlow. • Knowledge of the principles, algorithms, and techniques used in machine learning and video processing with first-hand experiences.
Preferred Qualifications
• PhD or Master degree in Machine Learning, Computer Science, Electrical/Computer Engineering, or related fields. • Knowledge of low-level vision algorithms including spatial and temporal image/video processing. • Experience working with multimodal and multimodal large language models (MLLMs) (e.g., image-text, video-audio systems). • Experience evaluating generative and multimodal models, including benchmarking and quality assessment. • Publication record in top-tier conferences (e.g., CVPR, ICCV, SIGGRAPH, ECCV, NeurIPS, ICML, ICLR) • Strong communication skills and documentation skills.