Job Description
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Description
The Hardware team features a collaborative environment with creative, smart talents, world-class products and cutting-edge technologies. The team provides opportunities for individuals to contribute across a wide spectrum of disciplines. Best-in-class engineering excellence and thoroughness are expected and encouraged. Innovation is highly supported and valued. Pushing the envelope to design and ship innovative products with best-in-class technologies and user experiences are the main goals of the Hardware Test Engineering (HWTE) team. This individual will play a key role in Machine Learning tools design and development to enable advanced anomaly reasoning and core manufacturing models. You will work closely with cross-functional groups to ensure the success of current and future Apple products.
Responsibilities
- Design, develop, and optimize core machine learning models and data architectures to support manufacturing processes.
- Develop advanced multimodal and LLM-based models for hardware test reasoning and analysis.
- Integrate core ML capabilities into central frameworks, ensuring seamless end-to-end functionality and system optimization.
- Collaborate with cross-functional teams to validate, debug, and deploy production-ready algorithms to real-world factory infrastructures.
Minimum Qualifications
- Currently pursuing a BS, MS, or PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Computer Vision, or a related field.
- Available to join internship for 3-6 months full-time.
- Solid foundation in machine learning algorithm development and data architecture, with deep knowledge of traditional ML algorithms and deep learning frameworks (PyTorch, TensorFlow).
- Strong programming skills in Python and ML libraries.
- Self-motivated, responsible, with excellent written and verbal interpersonal skills.
Preferred Qualifications
- Experience with Large Language Models (LLMs), prompt engineering, and multimodal data integration.
- Familiarity with computer vision and image processing for anomaly detection.
- Experience in data analysis, pipeline optimization, and system latency reduction.
- Familiarity with version control (Git), PRs, and collaborative software development.
