Machine Learning Architect - LLM & Generative AI (Image/Video)
Apple
Machine Learning Architect - LLM & Generative AI (Image/Video)
Job Description
The System Intelligence and Machine Learning (SIML) organization at Apple is looking for an experienced and visionary Machine Learning Architect 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. In this ML architect 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 .
Locations
- Seattle, Washington, United States 98117
Salary
Estimated Salary Rangemedium confidence
80,000,000 - 150,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Machine Learning Architectureintermediate
- Technology Strategyintermediate
- R&D Leadershipintermediate
- Large Language Models (LLMs)intermediate
- Generative AIintermediate
- Image Generationintermediate
- Video Generationintermediate
- Cross-Functional Collaborationintermediate
- Technical Roadmap Definitionintermediate
- Large-Scale Model Optimizationintermediate
- Hardware and Software Co-Designintermediate
- Diffusion Modelsintermediate
- Multi-Modal AIintermediate
- Generative Video Synthesisintermediate
- Scalable Architecture Designintermediate
- Model Trainingintermediate
- Model Optimizationintermediate
- Model Deploymentintermediate
- Fine-Tuningintermediate
- Reinforcement Learningintermediate
- Reward Strategiesintermediate
- Transfer Learningintermediate
- Multimodal Alignmentintermediate
- Prototyping Novel Techniquesintermediate
- Mentorshipintermediate
- Technical Excellenceintermediate
Required Qualifications
- Masters, or Ph.D. in Computer Science, or Computer Engineering; similarly related fields, or comparable professional experience (experience)
- Proficiency in toolkits like PyTorch or other deep learning frameworks (experience)
- 15+ years in machine learning, with at least 2 years of experience in LLMs, diffusion models, or other generative image/video models (experience, 15 years)
- Experience in distributed training, model parallelism, and deployment of large-scale generative models (experience)
- Knowledge of techniques such as quantization, distillation, and efficient inference. Experience with deploying large ML models in real world products (experience)
- Strong background in conducting experiments, analyzing results, and iterating on model improvements. (experience)
Preferred Qualifications
- Experience in multi-modal models (e.g., image, video, audio, or motion modalities) (experience)
- Familiarity with emerging technologies such as Mixture of Experts, LoRA, and Retrieval Augmented Generation (experience)
- Strong academic track record with publications in top tier conferences (NeurIPS, CVPR, ICLR, etc) (experience)
Responsibilities
- In this ML architect 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 .
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Answer 10 quick questions to check your fit for Machine Learning Architect - LLM & Generative AI (Image/Video) @ Apple.
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Machine Learning Architect - LLM & Generative AI (Image/Video)
Apple
Machine Learning Architect - LLM & Generative AI (Image/Video)
Job Description
The System Intelligence and Machine Learning (SIML) organization at Apple is looking for an experienced and visionary Machine Learning Architect 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. In this ML architect 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 .
Locations
- Seattle, Washington, United States 98117
Salary
Estimated Salary Rangemedium confidence
80,000,000 - 150,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Machine Learning Architectureintermediate
- Technology Strategyintermediate
- R&D Leadershipintermediate
- Large Language Models (LLMs)intermediate
- Generative AIintermediate
- Image Generationintermediate
- Video Generationintermediate
- Cross-Functional Collaborationintermediate
- Technical Roadmap Definitionintermediate
- Large-Scale Model Optimizationintermediate
- Hardware and Software Co-Designintermediate
- Diffusion Modelsintermediate
- Multi-Modal AIintermediate
- Generative Video Synthesisintermediate
- Scalable Architecture Designintermediate
- Model Trainingintermediate
- Model Optimizationintermediate
- Model Deploymentintermediate
- Fine-Tuningintermediate
- Reinforcement Learningintermediate
- Reward Strategiesintermediate
- Transfer Learningintermediate
- Multimodal Alignmentintermediate
- Prototyping Novel Techniquesintermediate
- Mentorshipintermediate
- Technical Excellenceintermediate
Required Qualifications
- Masters, or Ph.D. in Computer Science, or Computer Engineering; similarly related fields, or comparable professional experience (experience)
- Proficiency in toolkits like PyTorch or other deep learning frameworks (experience)
- 15+ years in machine learning, with at least 2 years of experience in LLMs, diffusion models, or other generative image/video models (experience, 15 years)
- Experience in distributed training, model parallelism, and deployment of large-scale generative models (experience)
- Knowledge of techniques such as quantization, distillation, and efficient inference. Experience with deploying large ML models in real world products (experience)
- Strong background in conducting experiments, analyzing results, and iterating on model improvements. (experience)
Preferred Qualifications
- Experience in multi-modal models (e.g., image, video, audio, or motion modalities) (experience)
- Familiarity with emerging technologies such as Mixture of Experts, LoRA, and Retrieval Augmented Generation (experience)
- Strong academic track record with publications in top tier conferences (NeurIPS, CVPR, ICLR, etc) (experience)
Responsibilities
- In this ML architect 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 .
Tags & Categories
Answer 10 quick questions to check your fit for Machine Learning Architect - LLM & Generative AI (Image/Video) @ Apple.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs