Sr. Machine Learning Engineer

The Answers, Knowledge and Information Team is building the next-generation of machine learning solutions for Knowledge Q&A at Apple and help power features including Siri, Safari and Spotlight. The features we build are redefining how hundreds of millions of people use their computers and mobile devices to search and find what they are looking for. As part of our team, you will be leveraging and improving upon the latest advancements in machine learning and software engineering to understand user queries and intents, retrieve and rank documents and generate helpful answers and work on horizontal areas such as internationalization and safety.

Description

As a member of our fast-paced group, you’ll have the unique and rewarding opportunity to shape upcoming products from Apple. Our team works on a search platform that powers features that incorporate search into Apple products including but not limited to Siri, Spotlight, Safari. We specifically own the real-time domains of this search platform. We are looking for candidates who have both strong software engineering skills and strong domain knoweldgewith applied machine learning experience and strong software engineering skills.

Minimum Qualifications

Experience working on both software development and building ML models
Experience developing software in Go or other object-oriented languages
3+ years of experience developing software
Experience with utilizing PyTorch, TensorFlow, or JAX for training and deploying deep learning models
Understanding product requirements then translating them into modeling tasks and engineering tasks
BS in Computer Science, Artificial Intelligence, Machine Learning, Information Retrieval, Data Science or related field or equivalent work experience

Preferred Qualifications

Experience working on search ranking, relevance, recommendation or information retrieval
MS or PhD in Computer Science, Artificial Intelligence, Machine Learning, Information Retrieval, Data Science or related field or equivalent work experience
Experience with cloud-native deployment (e.g. Kubernetes)
Experience with continuous integration and continuous development solutions (e.g. Jenkins, etc.)