AIML - Staff Machine Learning Engineer, Answers Knowledge and Information

Job Description

Join Apple's Applied ML team to work on large scale machine learning and deep learning research and development to improve Open Domain Question Answering and Summarization.

Requirements

• 10+ years of ML experiences in search, natural language processing/understanding, Conversational AI
• Proven experience for LLM post training, including but not limited to SFT, RLHF, RLAIF, Reward Modeling, Chain-of-thought, agentic LLM
• Hands-on experience building RL pipelines and training agents in simulation or real-world environments
• Growth mindset and ability to learn new technologies
• MS or Ph.D. in Computer Science, Machine Learning with a specialty in reinforcement learning, or a related field

Responsibilities

• Designing and developing advanced Reinforcement Learning technologies in the post-training of generative model, and delivering the end-user experience
• Driving cross-functional technical initiatives, collaborating with research, engineering and production teams to translate theoretical advances into deployable systems
• Developing novel and cutting-edge RL algorithms and improving existing ones
• Staying up to date with the latest RL research and integrate best practices into the team's workflow
• Working on the end-to-end ML lifecycle: algorithm design and implementation, data collection, model training, evaluation, and deployment

Benefits

• 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.