Machine Learning Engineer
Lex
Software Engineering
Singapore
Posted on Mar 14, 2026
Summary
The 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 pre-training data curation to post-training data preparation in a large-scale, to help deliver new features for Apple products and bring high impact to millions of users.
Description
Join us as an ML 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.
Responsibilities
The 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 pre-training data curation to post-training data preparation in a large-scale, to help deliver new features for Apple products and bring high impact to millions of users.
Description
Join us as an ML 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.
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
- Master’s degree in Machine Learning, Computer Science, Electrical/Computer Engineering, or related fields
- Knowledge of the principles, algorithms, and techniques used in machine learning and video processing with first-hand experiences
- Strong experience in evaluating supervised, unsupervised, and deep learning models
- Familiarity with multimodal models (e.g., image + text, video + audio) and related evaluation challenges
- Proficiency in Python and libraries such as NumPy, pandas, scikit-learn, PyTorch, or TensorFlow
- Strong communication skills and documentation skills
- PhD degree in Machine Learning, Computer Science, Electrical/Computer Engineering, or related fields
- Knowledge of low-level vision algorithms such as spatial and temporal image/video processing
- Publication record in top-tier conferences (e.g., CVPR, ICCV, SIGGRAPH, ECCV, NeurIPS, ICML, ICLR)
- Experience evaluating generative models (e.g., text generation, image/video generation)
- Excellent independent problem-solving skills
- Hands-on experience working on MLLMs