About the role

Aplyr's Quick Take

This role is for a Machine Learning Engineer focused on developing video processing features using machine learning algorithms. You'll be hands-on with data curation, model development, and collaborating with various teams to enhance Apple products. It's primarily an individual contributor position.

Good fit

Ideal candidates have at least 3 years of experience in machine learning and video processing, with strong Python skills. A background in computer science or engineering, along with a collaborative work style, will help you thrive here.

Worth noting

The position requires familiarity with both traditional and deep learning models, and experience with multimodal systems is a plus. The emphasis on publications suggests a strong research component, which may not appeal to everyone.

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 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.

Description

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.

Minimum Qualifications

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.

Skills & Tags

go machine learning

Aplyr's read

Apple is a tech giant known for its sleek design and innovation, attracting top talent in engineering, design, and business operations.
Synthesized from recent postings & public sources

What's promising

•Apple consistently leads in tech innovation with a strong focus on design and user experience.
•The company's global brand recognition offers employees a prestigious platform for career growth.
•Apple's robust ecosystem integrates hardware, software, and services, creating diverse job opportunities.

What to watch

•High-pressure work environment with demanding deadlines can impact work-life balance.
•Apple's secretive culture may limit transparency and cross-departmental communication.
•Dependence on hardware sales makes the company vulnerable to market saturation risks.

Why Apple

•Apple's design philosophy emphasizes simplicity and elegance, setting it apart in the tech industry.
•The company has a unique retail presence with its own stores enhancing customer experience.
•Apple's closed ecosystem creates a seamless integration across its products, unmatched by competitors.

Aplyr’s read is generated by AI from public sources. Was it useful?

About Apple

Apple

apple.com

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AAPL$298.01+0.70%

Apple Inc. is a leading technology company known for its innovative consumer electronics, software, and services. The company designs and manufactures products such as the iPhone, iPad, Mac computers, and wearables, significantly influencing the tech industry and consumer behavior worldwide.