Internship Computer Vision & Machine Learning Research - LLM Efficiency

Apple; München; On-site; EUR 16,000 - 22,000; Part time

Job summary

Apple is seeking research interns in Munich to advance machine learning through frontier model efficiency, LLMs, and diffusion models. You will join world-class researchers and engineers, contribute to cutting-edge work across Apple ecosystems, and publish results in leading venues.

The role targets doctoral candidates focusing on ML; responsibilities span literature review, method development, prototype implementation, and large-scale experiments.

Qualifications

• Working towards a doctoral degree in computer science, engineering, data science, applied mathematics, or equivalent.
• 6 months dedication preferred; starting no later than March 2026.
• Proven research expertise in machine learning.
• Publication record in top conferences (e.g., NeurIPS, ICLR, ICML, COLM).
• Solid software engineering skills in multi-language systems; Fluency in Python.

Responsibilities

• Identify promising research opportunities and review state-of-the-art methods and literature.
• Craft novel research approaches and implement them as code prototypes.
• Plan and run large-scale experiments across multi-node, multi-GPU systems.
• Write a paper and push it through to submission.

Skills

Machine Learning

Python

Research

Publications

Experimentation

Education

PhD Candidate

Tools

PyTorch

TensorFlow

Job description

Summary

We're seeking research interns to create breakthrough innovations in machine learning. We are particularly interested in efficiency of frontier models, including LLMs and diffusion models. You will work in an organization of world-class machine learning researchers and engineers. Our work powers cutting-edge technologies across the Apple ecosystem and is published in the most selective scientific journals and conferences.

Description

You are in your final years of a PhD programme in Machine Learning and have already published some of your work at top-tier venues in the field. During your time with us, you will continue sharpening your research skills as we go through the various collaborative stages of an ML research project: Identifying a promising research opportunity, reviewing state-of-the-art methods and relevant literature, crafting novel approaches, implementing them as code prototypes, planning and running large-scale experiments across multi-node, multi-GPU systems, writing a paper, and seeing it through to submission.

Topics of interest include but are not limited to frontier models, efficiency of LLM inference and training, on-device models, speculative decoding, contextual sparsity, quantization and compression. We are a team of best-in-the-world research scientists and engineers with deep experience in computer vision, machine learning, robotics, computer graphics, and related areas. We work on exciting new technologies that bring joy to millions of people.

Values

• Passion for the mission: We're here to make something extraordinary. We seek whatever work is right and strive for the best possible results.
• Modesty: The right answer is more significant than being right. We search for solutions as a team and value clear-eyed feedback.
• Lean habits: You can't grow without limits. Time constraints and big goals encourage us to sharpen our focus and learn to make phenomenal decisions.

Minimum Qualifications

• You are working towards a doctoral degree in computer science, engineering, data science, applied mathematics, or equivalent.
• 6 months dedication is preferred, and starting no later than March 2026
• Proven research expertise in machine learning.
• Publication record in relevant conferences (e.g., NeurIPS, ICLR, ICML, COLM, etc).
• Solid software engineering skills in complex, multi-language systems. Fluency in Python.

Preferred Qualifications

• Expertise in ML algorithms and top practices for working with deep learning systems
• Proficiency with ML modeling frameworks (PyTorch, Tensorflow, etc.)
• Strong overall software development approach. You deliver clean, well-tested code.

At Apple, we're not all the same. And that's our greatest strength. We draw on the differences in who we are, what we've experienced, and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. We will work with applicants to make any reasonable accommodations.

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace

Role Number: 200686569-1731