The Siri and Information Intelligence team at Apple is seeking a Machine Learning Engineer to join their world-class team of experts in large-scale data management and machine learning systems. This role is crucial in revolutionizing how hundreds of millions of people access information across Apple's ecosystem, including Siri, Spotlight, Safari, and Messages.
The position involves working in one of the most dynamic high-performance computing environments, handling petabytes of data and millions of queries per second. You'll be collaborating with renowned experts to enhance features across Apple's products, focusing on question answering, assistant response ranking, summarization, and search technologies.
As a Machine Learning Engineer on the Search and Knowledge Quality Team, you'll be responsible for designing and developing cutting-edge features for platforms involving large-scale data management, machine learning, and deep learning systems. You'll work with various data types including graph data, web documents, and both semi-structured and unstructured data feeds.
The role offers an opportunity to shape upcoming Apple products by leveraging applied machine learning expertise and robust software engineering skills. Working alongside a diverse team of applied scientists and distributed systems engineers, you'll contribute to refining user search experiences and ensuring they meet users' information-seeking needs effectively.
Key responsibilities include developing machine learning models, implementing end-to-end pipelines, and working with large-scale data sets. You'll need expertise in programming languages like Python, C++, and Go, plus experience with machine learning frameworks and cloud-native deployments.
The position offers competitive compensation including base pay between $143,100 and $264,200, plus additional benefits such as stock options, comprehensive medical coverage, and education reimbursement. This is an excellent opportunity for someone passionate about machine learning and AI to make a significant impact on products used by millions of people daily.