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Apple ML Researcher - Multimodal LLM 
United States, California, Sunnyvale 
187745610

21.04.2025
We are looking for a candidate with a strong background in developing foundation models and multimodal large language models (LLMs) that integrate various types of data such as text, audio and video. You will not only work on cutting-edge projects to advance our AI capabilities, but also contribute to practical features in Apple products and bring impact to millions of users. You will collaborate with others to drive data requirements, validation strategies, and key performance indicators, and conduct algorithm research and development that serves product needs. A successful candidate will stay up-to-date with the latest advancements in AI, machine learning, and computer vision, applying this knowledge to drive innovation— but also take a practical approach to problem solving and software engineering to deliver clean, modular, testable code.
  • BS and a minimum of 3 years relevant industry experience
  • Strong software engineering skills and proficiency in Python and PyTorch.
  • Capable of making well-informed and practical decisions in a rapidly evolving environment.
  • Excellent communication and experience working with multi-functional teams.
  • Self-motivated with proven track record to optimally prioritize and deliver tasks on schedule.
  • Curiosity and willingness to learn new things in order to improve the quality of their solutions.
  • MS or PhD in computer vision, computer graphics, machine learning, computer science, computer engineering or related fields.
  • Strong proficiency in C/C++.
  • Experience in developing, training/tuning foundation models and multimodal LLMs.
  • Experience with training and troubleshooting generative architectures such as diffusion, flow matching, or normalizing flow at scale.
  • Experience applying reinforcement learning to help train foundation models a plus.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.