Apple Maps and the thousands of applications it empowers are being used by millions every single day! As a fundamental tool for human activity, Maps technology is evolving and new techniques are emerging.
We are looking for a Machine Learning Engineer to join and help play a big part in the next revolution of Maps; to enable users to find more things in innovative ways. On our team, you will have plenty of opportunities to build groundbreaking technologies using ML and GenAI at scale to improve the search quality for Apple Maps.
Description
The goal of Maps Search team is to take Apple’s Maps to the next level of intelligence and accuracy using machine learning and artificial intelligence techniques. Engineers and scientists on our team work on a wide spectrum of approaches to improve search experiences on Apple Maps.
Responsibilities
Develop and optimize ML algorithms to handle key issues in local search: query understanding, intent modeling, ranking and semantic search Design and develop tools, processes and analytics for backend data-extraction pipelines - along with performing hands-on analyses to answer hard hypotheses/questions. Collaborate with various teams (e.g., infrastructure, quality, data) to develop exciting features and contribute towards our mission of best search experience to our end-users. Develop and mentor aspiring applied scientists / engineers to expand their scope and have a big impact. Be part of building a world class search team!
Minimum Qualifications
MS in computer science or equivalent field Proven record in delivering end-user facing ML driven products Strong programming experience in one or more of the following: Java, C++, Python Knowledge and experience with one of Tensorflow/Pytorch/Jax frameworks. Excellent interpersonal and communication skills - working independently and/or in small teams Attention to detail, data accuracy and quality of output
Preferred Qualifications
Ph.D in computer science or equivalent field Expertise and experience in various facets of machine learning and natural language processing, such as classification, feature engineering, information extraction, clustering, semi-supervised learning, topic modeling and ranking Practical understanding of the mathematics behind modern machine learning, linear algebra and statistics. Good knowledge of big data processing, prior experience with Hadoop, Spark, Hive is highly desired. Knowledge and prior experience with some deep learning and GenAI frameworks and LLMs are desired. Prior experience in consumer facing product is desired. Prior team lead experience is desired.
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