Apple AI/ML - Data Engineer (Speech Recognition), Siri and Language Technologies in Cambridge, Massachusetts
AI/ML - Data Engineer (Speech Recognition), Siri and Language Technologies
Machine Learning and AI
2-5+ 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/Iceberg, Spark, Trino, Druid, Solr, Flink, 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.
The ideal candidate will have outstanding communication skills, proven data infrastructure design and implementation capabilities, strong eye for business, and a highly developed drive to deliver results. You 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 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 outstanding 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
Meeting any of the additional requirements is considered a plus:
- Hands-on experience with ASR or NLP toolkits.
- Hands-on experience with deep learning toolkits such as TensorFlow, PyTorch, etc.
- Hands-on experience building and deploying production AI/ML systems.
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