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Machine Learning Architect Manager , LLM & Generative AI
Apple
H1B ✓On-sitemanagerPosted March 30, 2026
About the Role
This role involves defining the technical roadmap for improving the quality and performance of Large Language Models and generative models, while leading R&D initiatives in areas like large-scale model optimization and multi-modal AI. The manager will also develop scalable architectures for training and deploying these large models and mentor engineering teams.
Requirements
Candidates must possess a Master's or Ph.D. in a relevant field or comparable experience, along with over 15 years in machine learning, including at least 2 years focused on LLMs or generative models. Proficiency in deep learning toolkits like PyTorch and experience with distributed training, model parallelism, and efficient inference techniques are required.
Full Job Description
The System Intelligence and Machine Learning (SIML) organization at Apple is looking for an experienced and visionary Machine Learning Architect Manager to drive technology direction, shape our machine learning strategy, and lead pioneering R&D efforts. In this role, you will define and guide the development of technologies focusing on improving both the quality and performance of advanced large language models (LLMs) and generative AI models for image and video generation. You will work closely with cross-functional teams, including researchers, engineers, and product leaders, to deliver cutting-edge AI solutions that push the boundaries of generative technologies both on cloud and on edge devices that reach billions of users.
Description
In this ML architect manager role, the key responsibilities include: Technology Strategy & Direction: Define the technical roadmap for improving the quality and performance in LLMs and generative models, ensuring alignment with business objectives. Technology and Industry Leadership: Lead R&D initiatives in areas such as large-scale model optimization, hardware and software co-design, diffusion models, multi-modal AI, and generative video synthesis. Stay up-to-date with advancements in Generative AI to incorporate emerging technologies into our solutions. Architecture Design: Develop scalable, efficient architectures for training, optimizing, and deploying large-scale LLMs and generative models. Innovation and Experimentation: Explore and prototype novel techniques in generative AI, including fine-tuning, reinforcement learning with various of reward strategies, transfer learning, and multimodal alignment. Collaboration and Mentorship: Partner with rest of Apple teams to transition technology breakthroughs into production grade solutions. Guide and mentor machine learning engineers and researchers to foster technical excellence .
Minimum Qualifications
Masters, or Ph.D. in Computer Science, or Computer Engineering; similarly related fields, or comparable professional experience
Proficiency in toolkits like PyTorch or other deep learning frameworks
15+ years in machine learning, with at least 2 years of experience in LLMs, diffusion models, or other generative image/video models
Experience in distributed training, model parallelism, and deployment of large-scale generative models
Knowledge of techniques such as quantization, distillation, and efficient inference. Experience with deploying large ML models in real world products
Strong background in conducting experiments, analyzing results, and iterating on model improvements.
Preferred Qualifications
Experience in multi-modal models (e.g., image, video, audio, or motion modalities)
Familiarity with emerging technologies such as Mixture of Experts, LoRA, and Retrieval Augmented Generation
Strong academic track record with publications in top tier conferences (NeurIPS, CVPR, ICLR, etc)
Description
In this ML architect manager role, the key responsibilities include: Technology Strategy & Direction: Define the technical roadmap for improving the quality and performance in LLMs and generative models, ensuring alignment with business objectives. Technology and Industry Leadership: Lead R&D initiatives in areas such as large-scale model optimization, hardware and software co-design, diffusion models, multi-modal AI, and generative video synthesis. Stay up-to-date with advancements in Generative AI to incorporate emerging technologies into our solutions. Architecture Design: Develop scalable, efficient architectures for training, optimizing, and deploying large-scale LLMs and generative models. Innovation and Experimentation: Explore and prototype novel techniques in generative AI, including fine-tuning, reinforcement learning with various of reward strategies, transfer learning, and multimodal alignment. Collaboration and Mentorship: Partner with rest of Apple teams to transition technology breakthroughs into production grade solutions. Guide and mentor machine learning engineers and researchers to foster technical excellence .
Minimum Qualifications
Masters, or Ph.D. in Computer Science, or Computer Engineering; similarly related fields, or comparable professional experience
Proficiency in toolkits like PyTorch or other deep learning frameworks
15+ years in machine learning, with at least 2 years of experience in LLMs, diffusion models, or other generative image/video models
Experience in distributed training, model parallelism, and deployment of large-scale generative models
Knowledge of techniques such as quantization, distillation, and efficient inference. Experience with deploying large ML models in real world products
Strong background in conducting experiments, analyzing results, and iterating on model improvements.
Preferred Qualifications
Experience in multi-modal models (e.g., image, video, audio, or motion modalities)
Familiarity with emerging technologies such as Mixture of Experts, LoRA, and Retrieval Augmented Generation
Strong academic track record with publications in top tier conferences (NeurIPS, CVPR, ICLR, etc)