As a Staff Applied Scientist on the Siri team, you will be at the forefront of developing powerful large language models (LLMs) that enhance user interactions with devices. This role focuses on crafting UI control through innovative AI solutions that prioritize personalization and low-latency experiences. You will lead research and engineering efforts to advance model post-training techniques and ensure the successful delivery of ML-powered features. Collaboration with researchers and engineers is key to moving innovations from prototype to production.

• Masters or PhD in Computer Science, Machine Learning Engineering or equivalent professional experience
• 7+ years of hands-on industry experience with a proven track record of shipping ML-powered products or features, ideally involving LLMs
• Extensive experience with the ML development loop, including model architectures, data curation, training policies and evaluation
• Deep expertise in LLM/VLM post-training methods, including supervised fine-tuning and reinforcement learning
• Proficiency in Python and one of the deep learning frameworks such as PyTorch, JAX, or TensorFlow
• Excellent communication skills, including strong interpersonal, verbal and written abilities
• Experience developing AI agents capable of complex reasoning, planning, tool use and UI control in diverse environments
• Experience developing small LLMs for constrained or edge devices
• Experience building benchmarks and environments to evaluate UI control agents
• Deep understanding of model efficiency and deployment trade-offs in production environments
• Experience with multi-modal foundation models
• Experience developing ML systems for natural language understanding or digital assistants

• Drive the design, development and delivery of large language models that power Siri
• Lead research and engineering efforts in model post-training techniques
• Collaborate closely with researchers, software engineers and product teams
• Identify and apply post-training techniques to advance model efficiency
• Contribute to the end-to-end model lifecycle process
• Set technical directions for the team
• Emphasize rapid iteration and delivering impactful results

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.