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AIML - Foundation Model Post-Training Research Scientist

Apple· Machine Learning and AI
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Zurichfull-timePosted 1mo ago

About the role

Senior AI/ML researcher role focused on post-training research for foundation models within Apple’s Core Foundation Models team. Lead progress in large-scale language models with emphasis on reinforcement learning, planning, reasoning, and agentic intelligence, spanning the full AI development pipeline from architecture design to deployment across billions of devices.

Responsibilities

  • Lead transformative progress in large-scale language models with a strong focus on reinforcement learning.
  • Develop and apply RL techniques to train and refine next-generation foundation models.
  • Work across the entire AI development pipeline—from designing multi-modal architectures to advancing decision-making, evaluation, and large-scale deployment to billions of devices worldwide.
  • Collaborate with researchers and systems engineers to advance foundation models on capabilities critical to Apple Intelligence products (e.g., coding, software engineering, device use, UI understanding and navigation, agentic search).

Qualifications

  • PhD/Master’s degree or equivalent experience in Computer Science, Computer Engineering, or a closely related field.
  • Deep expertise in generative AI architectures, with hands-on experience training and scaling large language models (LLMs) and/or multi-modal foundation models.
  • Industry experience in developing, training, and deploying large-scale ML systems, with emphasis on model performance optimization.
  • Demonstrated industry experience on developing agentic capabilities for modern foundation models.
  • Proficiency in Python and modern ML frameworks (PyTorch/JAX).
  • Proven ability to analyze data, diagnose bottlenecks, and optimize large-scale models for performance and efficiency, with creativity in solving complex technical challenges.
  • Strong critical thinking, collaboration, and communication skills, with the ability to convey complex concepts to both technical and non-technical stakeholders.
  • Background in deep learning and reinforcement learning, including practical experience applying these methods to LLMs and foundation models.
  • Demonstrated industry experience delivering ML-driven product features at scale.
  • Proven record in designing, training, and optimizing LLMs and/or multi-modal foundation models at scale.
  • Expert-level understanding of machine learning theory and practice, with specialization in generative modeling and large-scale architectures.
  • Research or applied experience in decision-making, reinforcement learning, and agentic reasoning.
  • Strong research track record, with peer-reviewed publications at leading AI/ML or NLP venues (e.g., NeurIPS, ICML, ICLR, ACL).

Skills

Required:PhD/Master’s degree or equivalent experienceGenerative AI architecturesLarge-scale language models (LLMs)Multi-modal foundation modelsReinforcement learningPythonPyTorch/JAXData analysis & optimizationCommunication & collaborationResearch/academic publications

Benefits

  • Accessibility-focused culture and accommodations for applicants.
  • Commitment to diversity and inclusion.
  • Benefits aligned with Apple’s workplace practices and accessibility initiatives.
Last updated Aug 28, 2026. Interested? Apply on the company site.

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