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Apple is seeking an experienced AI/ML researcher to join its foundation model team in Zurich. You will play a critical role in advancing large-scale frontier foundation models, with a focus on post-training strategies that transform raw model capabilities into highly capable, intelligent assistants powering billions of Apple products.
Key responsibilities include designing and iterating on end-to-end post-training strategies, including reinforcement learning approaches, to unlock specific model behaviors. You will pioneer novel algorithms for preference optimization, model steering, and safety mechanisms. A significant portion of your work involves driving data strategy—researching methods for high-quality human and synthetic data generation, automated data filtering, and curriculum learning to improve instruction following and reasoning capabilities.
You will design robust evaluation methodologies that move beyond static benchmarks to measure real-world performance in helpfulness, factuality, and utility. Close collaboration with pre-training teams will inform architectural choices, while partnerships with product teams will translate user requirements into concrete model capabilities.
The ideal candidate brings demonstrated expertise in deep learning with a focus on LLMs, post-training, or reinforcement learning, backed by strong academic or real-world accomplishments. You should be proficient in Python and major deep learning frameworks (JAX or PyTorch), with a Master's or PhD in Computer Science, Machine Learning, or related field (or equivalent practical experience).
Preferred qualifications include experience training state-of-the-art large models at scale, familiarity with distributed training challenges, experience improving model performance on complex reasoning tasks (math, coding, logic), knowledge of transformer architectures and their transformations, and strong cross-functional communication skills.
