AIML ML Researcher, AFM

We build frontier foundation models that power intelligent experiences at Apple. Our team works across the full training lifecycle: including pre-training foundation models and developing mid-training approaches that bridge general capability and task-specific performance. What makes our work distinct is that were engineering models specifically for Apple silicon and optimized for experiences that are private personal and deeply integrated into the OS. Were solving frontier problems in reward modeling to resist reward hacking handling sparse and delayed rewards in agentic settings and aligning models reliably across the spectrum from open-ended creative tasks to precise action-taking workflows. If youre drawn to hard problems where the research and the product are inseparable this is the team

We believe that the most interesting problems in deep learning research arise when we try to apply learning to real-world use cases and this is also where the most important breakthroughs come from. You will work with a close-knit and fast growing team of world-class engineers and scientists to tackle some of the most challenging problems in foundation models and deep learning including end-to-end voice interactions natural language processing and combining learning with knowledge.

Demonstrated expertise in deep learning with publication record in relevant conferences (e.g. NeurIPS ICML ICLR COLM ACL NAACL EMNLP CVPR ICCV ECCV KDD ACL ICASSP InterSpeech) or a track record in applying deep learning techniques to productsnProficient programming skills in Python and one of the deep learning toolkits such as JAX PyTorch or TensorflownAbility to work in a collaborative or equivalent practical experience in Computer Science or related technical field.

Code Large language modelsnExperience in building end-to-end voice modelsnExperience in speech recognitions and generationsnExperience in reinforcement learning on-policy distillationnExperience in post-training mid-training large language models