Machine Learning Research Intern

Description du poste:

Apple is seeking highly motivated and talented candidates to join its Research Internship Program. The team conducts cutting-edge research and development in machine learning, with a focus on foundation models, on-device ML, natural language processing, speech technologies, and optimization.As a research intern, you will work on challenging, real-world problems, contribute to innovative ML solutions that shape future Apple Intelligence features, and collaborate closely with product and engineering teams to translate research into impact. You will also have opportunities to engage with the academic community through publications, technical reports, and conference presentations.
As a Machine Learning Research Intern: 1. you will:Conduct research and develop novel machine learning methods to address complex technical challenges that directly impact Apple products and Apple Intelligence features. 2. Collaborate with cross-functional teams across research, engineering, and product to transfer and deploy AI/ML solutions 3. Receive technical mentorship and guidance, and contribute to research artifacts such as technical reports, publications, and conference presentations.
Currently pursuing or recently completed a PhD or Master's degree (or equivalent experience) in Machine Learning, Computer Science, Data Science, Statistics, Human-Computer Interaction, Natural Language Processing, or a related field. Strong foundation in one or more of the following areas: -Machine Learning fundamentals, including Deep Learning, Reinforcement Learning, Unsupervised and Self-Supervised Learning, on-device ML and related areas. -Speech and Natural Language Processing, including Speech Recognition, Text-to-Speech, Conversational and Multimodal Interaction, Machine Translation, Information Retrieval, Knowledge Graphs, or Computational Linguistics. -Demonstrated research ability through publications, preprints, or technical reports. -Strong programming skills in Python, C/C++, CUDA, or other GPGPU programming environments. -Experience with modern ML frameworks such as PyTorch or TensorFlow. -Excellent written and verbal communication skills.
Applied ML Expertise: Experience developing high-quality ML solutions with strong attention to scientific rigor, robustness, and user privacy. Product Mindset: Passion for translating research into impactful, user-centric products. Collaborative and Creative: Ability to work effectively in cross-functional teams while contributing innovative ideas. Adaptability: Comfort working in a fast-paced environment, balancing research exploration with product-driven timelines