Generative AI Research Engineer, Multimodal, Agent Modeling - SIML

Apple Inc. • Cupertino, CA

52d

About The Position

Are you passionate about Generative AI? Are you interested in working on groundbreaking generative modeling technologies to enrich billions of people? We are driving multiple initiatives focused on advancing generative models, and we are seeking candidates experienced in training, adapting and deploying large-scale generative models. This role emphasizes AI safety, multimodal understanding and generation, and the development of agentic systems that push the boundaries of what AI can achieve responsibly. We are the Intelligence System Experience (ISE) team within Apple's software organization. The team operates at the intersection of multimodal machine learning and system experiences. It oversees a range of experiences such as System Experience (Springboard, Settings), Image Generation, Genmoji, Writing tools, Keyboards, Pencil u0026 Paper, Generative Shortcuts - all powered by production scale ML workflows. Our multidisciplinary ML teams focus on a broad spectrum of areas, including Visual Generation Foundation Models, Multimodal Understanding, Visual Understanding of People, Text, Handwriting, and Scenes, Personalization, Knowledge Extraction, Conversation Analysis, Behavioral Modeling for Proactive Suggestions, and Privacy-Preserving Learning. These innovations form the foundation of the seamless, intelligent experiences our users enjoy every day. We are looking for research engineers to architect and advance multimodal LLM and Agentic AI technologies, ensuring their safe and responsible deployment in the real world. An ideal candidate will have the ability to lead diverse cross functional efforts spanning ML modeling, prototyping, validation and privacy-preserving learning. A strong foundation in machine learning and generative AI, along with a proven ability to translate research innovations into production-grade systems, is essential. Industry experience in Vision-Language multimodal modeling, Reinforcement and Preference Learning, Multimodal Safety, and Agentic AI Safety u0026 Security would be meaningful needs. SELECTED REFERENCES TO OUR TEAM'S WORK: https://arxiv.org/pdf/2507.13575 https://arxiv.org/pdf/2407.21075 https://www.apple.com/newsroom/2024/12/apple-intelligence-now-features-image-playground-genmoji-and-more/We are looking for a candidate with a proven track record in applied ML research. Responsibilities in the role will include training large scale-multimodal (2D/3D vision-language) models on distributed backends, deploying efficient neural architectures on device and private cloud compute, addressing emerging safety challenges to make the model/agents robust and aligned with human values. A key focus of the position is ensuring real-world quality, emphasizing model and agent safety, fairness, and robustness. You will collaborate closely with ML researchers, software engineers, and hardware and design teams across multiple disciplines. The core responsibilities include advancing the multimodal capabilities of large language models and strengthening AI safety and security for agentic workflows. On the user experience front, the work will involve aligning image and video content to the space of LLMs for visual actions and multi-turn interactions, enabling rich, intuitive experiences powered by agentic AI systems.Experience with building u0026 deploying AI agents, LLMs for tool use, and Multimodal-LLMsArray

Requirements

• Strong foundation in machine learning and generative AI
• Proven ability to translate research innovations into production-grade systems
• Experience with building u0026 deploying AI agents
• Experience with LLMs for tool use
• Experience with Multimodal-LLMs

Nice To Haves

• Industry experience in Vision-Language multimodal modeling
• Industry experience in Reinforcement and Preference Learning
• Industry experience in Multimodal Safety
• Industry experience in Agentic AI Safety u0026 Security

Responsibilities

• Training large scale-multimodal (2D/3D vision-language) models on distributed backends
• Deploying efficient neural architectures on device and private cloud compute
• Addressing emerging safety challenges to make the model/agents robust and aligned with human values
• Advancing the multimodal capabilities of large language models
• Strengthening AI safety and security for agentic workflows
• Aligning image and video content to the space of LLMs for visual actions and multi-turn interactions
• Enabling rich, intuitive experiences powered by agentic AI systems

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Computer and Electronic Product Manufacturing
• Education Level: No Education Listed
• Number of Employees: 5,001-10,000 employees