AIML - Machine Learning Research Engineer, Generative AI - AFM

Apple seeks a Senior Machine Learning Research Engineer in Zurich to advance Generative AI, focusing on reinforcement learning for foundation models and Apple Intelligence.

The company is looking for a specialist to join its Zurich-based Generative AI group, where the primary mission involves enhancing foundation models through advanced reinforcement learning techniques. This role directly influences core products like Siri, affecting billions of users worldwide, while requiring close coordination with research teams in Cupertino and New York.

Responsibilities

• Create and expand reinforcement learning strategies to boost reasoning capabilities, instruction adherence, and multi-turn dialogue quality in large language models, while minimizing hallucinations.
• Construct and train autonomous agents capable of tool usage, strategic planning, and API integration to perform tasks reliably.
• Develop reward models, evaluation metrics, datasets, and simulation environments for methods such as RLHF, RLAIF, and RLVF.
• Execute large-scale experiments, interpret data, and convert insights into both academic contributions and tangible product enhancements for Apple Intelligence.
• Work within a European team of approximately 35 experts, maintaining tight collaboration with US-based foundation model groups.

Requirements

• Possess an MSc, PhD, or comparable professional experience in Computer Science, Machine Learning, Electrical Engineering, or a closely related discipline.
• Demonstrate deep expertise in reinforcement learning and deep learning, including practical experience training large-scale models, especially LLMs.
• Show proficiency in Python and contemporary ML frameworks like PyTorch or JAX, with proven skills in distributed training.
• Exhibit strong interpersonal skills to collaborate across disciplines and explain complex technical ideas to diverse audiences.

Nice to have

• A record of publications in premier ML/AI conferences or equivalent impact through open-source projects or industry achievements.
• Practical background in implementing tool use, planning, retrieval mechanisms, and agentic integrations for LLMs.
• Experience in data curation, evaluation frameworks, and implementing safety or guardrail methodologies.
• Capability to design and run large-scale experiments and devise innovative solutions for difficult technical challenges.

About the company

The company is dedicated to pushing the boundaries of technology by contributing to state-of-the-art research in artificial intelligence and machine learning.

• Focus on advancing cutting-edge research in AI.