Play a part in building the next revolution of machine learning technology. We're looking for passionate junior and mid-level researchers to work on ambitious curiosity-driven long-term research projects that will impact the future of Apple, and our products.
Requirements
- Demonstrated expertise in machine learning research working on at least some of the following topics - Reinforcement Learning, LLMs training, LLMs test-time adaptation/scaling, Reasoning/Planning, Diffusion Language Models, Audio Generative/Recognition Models, and Multimodal generative models.
- Publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR, ICCV, ECCV, ACL, EMNLP, etc)
- Hands-on experience working with deep learning toolkits such as Tensorflow or PyTorch.
- Strong mathematical skills in linear algebra and statistics.
- Ability to formulate a research problem, design, experiment, implement and communicate solutions.
- Hands on experience on at least some of the following: Torch Titan or Lingua, Sharded models, FSDP, DDP, fine-tuning pipelines for common models such as Llama, Mixtral, etc
Responsibilities
- advance the frontier of machine learning through a combination of self-directed research - proposing your own research ideas and demonstrating their feasibility, and collaborative research working with your colleagues on larger problems, sharing implementation and experimentation.
- provide technical mentorship and guidance, and prepare technical reports for publication and conference talks.
- collaborate with broader teams across Apple.
- work on innovative foundational research in machine learning.
- publish some of your results in high-quality scientific venues.
- make sure that your research results are of high quality and reproducible.
Other
- work on ambitious curiosity-driven long-term research projects that will impact the future of Apple, and our products.
- collaborate with world-class machine learning engineers and researchers to impact the future of Apple products
- Ability to work in a diverse collaborative environment.
- PhD, or equivalent practical experience, in Computer Science, or related technical field.
