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Internship Computer Vision & Machine Learning Research - LLM Efficiency

Apple· Machine Learning and AI
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Hybrid (Munich)internshipPosted 3w ago

About the role

Research internship focusing on efficiency of frontier models (LLMs and diffusion models) within Apple’s ML research organization. Students work through the full ML research lifecycle, from identifying opportunities and literature review to prototyping, large-scale experiments, and writing/submitting papers.

Responsibilities

  • Identify promising research opportunities and review state-of-the-art methods and literature
  • craft novel approaches and implement them as code prototypes
  • plan and run large-scale experiments across multi-node, multi-GPU systems
  • write a paper and see it through to submission
  • collaborate with world-class ML researchers and engineers
  • work on frontier models, efficiency of LLM inference and training, on-device models, speculative decoding, contextual sparsity, quantization and compression

Qualifications

  • You are in your final years of a PhD programme in Machine Learning
  • Proven research expertise in machine learning
  • Publication record in conferences (e.g., NeurIPS, ICLR, ICML, COLM)
  • Solid software engineering skills in complex, multi-language systems; Fluency in Python
  • Expertise in ML algorithms and best practices for deep learning systems
  • Proficiency with ML modeling frameworks (PyTorch, TensorFlow)
  • Strong software development approach with clean, well-tested code
  • Starting no later than March 2026; 6 months dedication preferred
  • Working towards a doctoral degree in computer science, engineering, data science, applied mathematics, or equivalent

Skills

Required:PhD in progress or completionResearch publicationPythonML frameworksSoftware engineering
Last updated Oct 2, 2026. Interested? Apply on the company site.

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