AI/ML – Data Scientist (Machine Learning & Natural Language), Siri Understanding


Job Overview

Key Qualifications

  • Expertise in natural language processing and machine learning, such as classification, feature engineering, information extraction, structured prediction, clustering, semi-supervised learning, topic modeling, and ranking.
  • Proficiency in data science and analytics, including statistical analyses and A/B testing Experience designing, conducting, analyzing, and interpreting experiments and investigations. Strong programming skills, expert knowledge of algorithms and data structures (Python, Java, or equivalent)
  • Excellent problem solving, critical thinking, creativity, organizational, design, and interpersonal skills; ability to work well with all levels of engineers. Confirmed ability to handle multiple projects with strict deadlines
  • Prior experience with applying Big Data tools (MapReduce, Hadoop, Hive and/or Pig, Spark) to large quantities of textual data is desired
  • Description

    The goal of the Siri Machine Learning & Natural Language team is to take Siri to the next level of intelligence and accuracy using advanced statistical techniques. The Data Scientist role in this team has a spectrum of approaches to improving Siri. At one end, we work on deriving key insights from large amounts of usage data to suggest new features and fundamental improvements to the user experience. At the other end, you would work on core machine learning algorithms and systems that are part of Siri’s ability to understand and respond to requests. You should be passionate about building outstanding products. This position involves a wide variety of skills and innovation. This is an unusual opportunity that sits at the cutting-edge of various disciplines such as data science and machine learning, and your work will have a huge impact on hundreds of millions of users across the globe.

    Education & Experience

    Master’s or PhD in Computer Science, Linguistics, a data-driven physical science, or equivalent

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