Internship - Machine Learning (Foundation Models)

Apple, Inc.; Zürich; On-site; CHF 22,000 - 45,000; Part time

Job summary

Apple, Inc. in Zürich, Switzerland seeks a research intern to advance foundation models with a focus on agentic capabilities and reinforcement learning. You will work with an applied ML team of about 35 engineers in Zurich and collaborate with US experts.

You will research, develop, and transfer results to real-world performance at scale, contributing to Apple Intelligence and potential product deployment across devices worldwide.

Qualifications

• PhD student in Machine Learning (Computer Science, Electrical & Computer Engineering, Statistics, Math, Natural Sciences, or related fields).
• Strong background in Reinforcement Learning and Deep Learning, with hands-on experience training large models, especially LLMs.
• Experience with training methodologies including pre-training, fine-tuning, and alignment approaches.
• Strong programming skills. Most relevant are Python, PyTorch, and JAX.

Responsibilities

• Research and develop novel approaches for enhancing foundation model capabilities.
• Leverage state-of-the-art, large-scale RL methods to improve reasoning and planning, multi-turn conversations, and general agentic capabilities.
• Design and train agents with tool calling, planning, and API integration to reliably complete tasks.
• Investigate multimodal foundation models spanning text, vision, audio, and other modalities.
• Collaborate on model alignment, safety, and responsible AI practices.
• Contribute to the development of tools and frameworks for foundation model experimentation and evaluation.

Skills

Reinforcement Learning

Deep Learning

Large-Scale training

Python

PyTorch

JAX

Education

PhD student in Machine Learning

Tools

Python

PyTorch

JAX

Job description

Internship - Machine Learning (Foundation Models)

We are looking for a machine learning research intern with passion to spearhead new solutions to challenging problems in foundation model development with an emphasis on agentic capabilities and Reinforcement Learning. You will closely work with an applied ML team of around 35 engineers in Zurich, and get the chance to connect with other experts in the US.

Description

During your internship, you will do research and development in the context of Apple foundation models that power next-generation AI experiences across Apple’s platforms. You will learn what is relevant to transfer results from machine learning research to meaningful real-world performance at scale. Your work can contribute to Apple Intelligence and be shipped to billions of devices, worldwide.

Responsibilities

• Research and develop novel approaches for enhancing foundation model capabilities
• Leverage state-of-the-art, large-scale RL methods to improve reasoning and planning, multi-turn conversations, and general agentic capabilities.
• Design and train agents with tool calling, planning, and API integration to reliably complete tasks.
• Investigate multimodal foundation models spanning text, vision, audio, and other modalities
• Collaborate on model alignment, safety, and responsible AI practices
• Contribute to the development of tools and frameworks for foundation model experimentation and evaluation

Minimum Qualifications

• PhD student in Machine Learning (Computer Science, Electrical & Computer Engineering, Statistics, Math, Natural Sciences, or other related fields)
• Strong background in Reinforcement Learning and Deep Learning, with hands-on experience training large models, in particular LLMs
• Experience with training methodologies including pre-training, fine-tuning, and alignment approaches
• Strong programming skills. Most relevant are Python, PyTorch, and JAX

Preferred Qualifications

• Excellent problem solving, critical thinking, and interpersonal skills.
• Ability to define and drive ambitious goal-oriented research and development independently

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.

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