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Apple
Bachelor
The people here at Apple don’t just build products — they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that encourage the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple and help us leave the world better than we found it. Imagine what you could do here. At Apple, new insights have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.
Responsible for leading ML and LLM-based tool and solution development to increase test engineers working efficiency and empower end-to-end optimization of test procedure.
Interact with internal groups at Apple to ensure a synchronization on the understanding of solution expectation and sufficient cross-team cooperation to secure a successful delivery.
This position requires ability to deal with dynamic and fast-paced environment requiring decision-making with ambiguous information.
Minimum Qualifications: BS or MS degree in computer science/Automation/Mechanical or Electronics Engineering.
Proven hands-on experience in modern machine learning pipelines and architectures.
Mastering data collection, machine learning modeling development, and run-time challenges.
Good experience or knowledge on manufacturing test or process at mass production.
Good communication skills with proficient spoken and written in both English and Chinese.
Preferred Qualifications: Aspiration and experience in quickly picking up domain knowledge including product technology and test metrology , exploring, designing and implementing ML solutions to solve realistic pain points.
Excellent analytical and problem solving skills.
Proven track record to work in a quick changing environment, independently and to deliver high quality solutions to tight schedules.
ML solution experience within or related to manufacturing industry
Solid experience in multiple ML areas, including but not limited to parametric data mining, time series analysis and prediction, anomaly detection, Large-Language-Model (LLM) tuning, prompt engineering, Retrieval Augmented Generation (RAG) solution optimization and Agent framework.