16 hours ago
Responsibilities
- Design and iterate on end-to-end post-training strategies, including reinforcement learning, to produce targeted model behaviors.
- Develop algorithms for preference optimization, model steering, and model safety.
- Research human and synthetic data generation, automated data filtering, and curriculum learning methods.
- Design evaluation methodologies measuring model helpfulness, factuality, utility, and real-world performance.
- Collaborate with pre-training teams on architecture choices and product teams on translating user requirements into model capabilities.
Requirements
- Demonstrated expertise in deep learning focused on LLMs, post-training, or reinforcement learning, supported by significant academic or real-world accomplishments.
- Proficient programming skills in Python and a major deep learning framework such as JAX or PyTorch.
- Master’s degree or PhD in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience.
- Preferred experience training state-of-the-art large models at scale and understanding distributed training challenges and trade-offs.
- Preferred experience improving model performance on math, coding, or logic reasoning tasks.
- Preferred familiarity with transformer architectures and their transformations.
- Strong communication skills and ability to work cross-functionally across Research and Product teams.
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.