The Apple Knowledge Quality Team is seeking extraordinary Machine Learning engineers to develop next-generation machine learning solutions for Knowledge Q&A, impacting features like Siri and Spotlight. This role involves working with large-scale data management and machine learning systems, focusing on enhancing user experience through evaluation and analysis. Engineers will collaborate with cross-functional teams to redefine how users search and find information on their devices. The position offers the opportunity to work in a high-performance computing environment with vast amounts of data and queries.

• A degree in Computer Science, Machine Learning, or a related field with 2+ years of industry experience building production ML/AI systems, or a PhD degree in a related field.
• Proficiency in programming languages such as Python, Scala, and Go.
• Experience building and maintaining large-scale data systems and end-to-end ML pipelines in production, ideally using the Apache software stack.
• Hands-on experience with machine learning frameworks such as PyTorch or TensorFlow in production environments.
• Experience with natural language processing, statistical data analysis, and model evaluation methodologies.
• Demonstrated ability to collaborate with cross-functional teams including product, engineering, and data science.
• Experience with CI/CD pipelines, model deployment, and monitoring solutions.
• MS degree with 6+ years of industry experience building and scaling ML/AI systems, or PhD degree with 3+ years of industry experience in production ML environments.
• Proven track record designing, deploying, and maintaining large-scale distributed ML systems serving millions of queries per second.
• Experience with A/B testing, experimentation frameworks, and data-driven product iteration at scale.
• Experience designing human-in-the-loop evaluation pipelines and leveraging user feedback to improve model performance.
• Hands-on experience with LLM deployment, prompt engineering, fine-tuning, or other generative AI technologies in production.
• Experience building model monitoring, observability, and quality assurance systems for production ML services.
• Experience optimizing ML systems for latency, throughput, and cost at scale.
• Strong product intuition and ability to translate business requirements into technical solutions.

• Design and develop features for a platform that manages large-scale data and machine learning systems.
• Collaborate with cross-functional teams to enhance user experience and product evolution.
• Push the boundaries of Knowledge Question Answering in Siri.
• Inform product evolution through measurement, evaluation, and analysis of user experience.
• Build and maintain large-scale distributed ML systems serving millions of queries per second.
• Implement A/B testing and experimentation frameworks for data-driven product iteration.
• Design human-in-the-loop evaluation pipelines to leverage user feedback for model improvement.
• Deploy and fine-tune large language models and other generative AI technologies in production.
• Monitor and ensure the quality of production ML services.

• 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.