3 days ago
Responsibilities
- Develop novel algorithms and scalable systems for pretraining data curation, quality assessment, diversity, and optimization.
- Build robust infrastructure and large-scale data processing pipelines for massive training datasets.
- Design controlled experiments to evaluate the relationship between training data and foundation model capabilities.
- Investigate data filtering, deduplication, data mixture optimization, synthetic data generation, and model-based data evaluation approaches.
- Collaborate with model training researchers and translate research ideas into measurable improvements and scalable production systems.
Requirements
- Bachelor's, master's, or doctoral degree in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience.
- Strong Python programming skills and experience developing production-quality software.
- Experience with large-scale data processing, distributed computing, or machine learning systems.
- Solid understanding of machine learning fundamentals and modern deep learning architectures.
- Strong analytical and problem-solving abilities with the capacity to independently investigate complex technical challenges.
- Preferred experience includes LLM pretraining, foundation model development, Spark, Ray, PyTorch, model training, experimental evaluation, scaling laws, training dynamics, synthetic data, and machine learning research or open-source contributions.
Tech Stack
Categories
AI ResearchML Engineering
About Apple
Apple designs and sells consumer electronics, software, and services for consumers and professionals worldwide, including iPhone, Mac, iPad, Apple Watch, and AirPods, plus platforms like iOS/macOS and services such as the App Store, iCloud, Music, and TV+. Its business combines device sales with services and subscriptions and in-house silicon design. Founded in 1976, Apple is headquartered in Cupertino, California, and trades on NASDAQ as AAPL.