Summary

Posted: Sep 17, 2020

Role Number:200162666

The Siri Web Answers team is redefining how hundreds of millions of people use their devices to get their questions answered. We are an R&D team pushing the limits of question answering technologies, responsible for a production service powering part of Siri. We are part of a wider effort to power search and answers across a variety of Apple products – including Siri, Spotlight, Safari, Messages, and more. As part of our team, you will be leveraging and improving upon the latest deep learning models in order to understand queries, rank documents, and find useful answers to users’ questions. Our team is responsible for deploying these models at scale, using the latest advances in model compression and inference-optimized hardware.

Key Qualifications

• 3+ years of experience in machine learning, deep learning, information retrieval, natural language processing or data mining
• Mastery of one of following languages: Python, Go, Java, C++
• Excellent interpersonal skills; ability to work independently as well as in a team
• Excellent knowledge and good practical skills in major machine learning algorithms
• Excellent data analytical skills
• Experience with large scale search and machine learning systems is highly desired
• Experience with Hadoop, Hive, and/or Impala is a plus
• Strong background in algorithms and data structures

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 includes a diversity of backgrounds, from applied scientists with a focus in NLP to experienced distributed systems engineers. As such, we are looking for candidates with applied machine learning experience and solid engineering skills. This role will have the following responsibilities: • Analyzing search ranking and relevance requirements, issues and opportunities • Understanding product requirements, then translating them into modeling tasks and engineering tasks • Building machine-learned models for search relevance, ranking, query understanding, and questioning • Building an end-to-end production service for question answering • Utilizing Spark, Hadoop MapReduce, Hive, Impala to perform distributed data processing pipelines • Utilizing PyTorch for training deep learning models.

Education & Experience

MS or Ph.D in Computer Science, Machine Learning or related field