AI/ML – Sr Data Engineer (Speech Recognition), Siri Understanding

Apple
Apple

Job Overview

Key Qualifications

  • 4+ years of experience in data engineering.
  • Expertise with ETL theory, process and technology.
  • Experience engineering metrics and statistical information out of massive and complex datasets (e.g. Hive, Spark MLlib, Druid, Solr, Kafka).
  • Proficiency in at least one programming language (preferably Python) and with developing code within a team environment (e.g. git, testing, code reviews).
  • Experience building robust data and analytic pipelines with a keen eye for where to automate (e.g. Oozie, Airflow).
  • Solid understanding of both relational and NoSQL database technologies.
  • Experience with visualization, data mining, or statistical tools.
  • Description

    The ideal candidate will have outstanding communication skills, proven data infrastructure design and implementation capabilities, strong business acumen, and an innate drive to deliver results. He/she will be a self-starter, comfortable with ambiguity and will enjoy working in a fast-paced dynamic environment. Responsibilities will include: – Building high-quality data pipelines and speech data tooling, implementing and operating with high reliability and availability.- Developing relationships with speech scientists and engineers, product managers and software engineers to understand data needs- Harden and launch new data models and data pipelines in production- Lead development of data tools to support analysis and data resources to support new product launches – Coordinate the delivery of insightful dashboards and other monitoring/analysis tools – Establish SLA’s for all data sets and processes running in production – Excellent writing and interpersonal skills – Thorough knowledge of macOS and iOS is helpful – Ability to stay focused and prioritize a heavy workload while achieving exceptional quality – You are upbeat, adaptable, and results-oriented with a positive attitude

    Education & Experience

    B.S., M.S., or PhD in Computer Science, Computer Engineering, or equivalent practical experience

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