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Apple AIML - Machine Learning Engineer, Siri Information and Intelligence in Cambridge, Massachusetts

AIML - Machine Learning Engineer, Siri Information and Intelligence

Cambridge,Massachusetts,United States

Machine Learning and AI

Would you like to play a part in the next revolution in human-computer interaction? Contribute to a product that is redefining mobile and desktop computing, and work with the people who built the intelligent assistant that helps millions of people get things done — just by asking? Create groundbreaking technology for large scale systems, spoken language, big data, and artificial intelligence. Join the Automatic Speech Recognition (ASR) team at Apple. The AIML ASR team is looking for exceptionally skilled and creative Scientists and Engineers eager to get involved in hands-on work improving the Siri experience.

Key Qualifications

  • 3-5+ years of experience in ML engineering, particularly in ML operations, data, model pipeline development or tooling

  • Experience with large-scale data processing and distributed systems.

  • Experience engineering metrics and statistical information out of massive and complex datasets (e.g. Hive/Iceberg, Spark, Trino, Druid, Solr, Flink, Kafka).

  • Strong coding skills in Python, C/C++, or Java, building software, and applying software engineering best practices (e.g. git, testing, CI/CD, scheduling).

  • Knowledge of Machine Learning concepts and toolkits (TensorFlow, PyTorch).

  • Experience building and deploying production AIML systems.

Description

You will be a part of a team that's responsible for a wide variety of speech-related data activities, including working with acoustic modeling, language modeling and tools developments teams to build data infrastructure and tooling to support both experimentation and production model pipelines. Our speech recognition research is very data driven, and we are passionate about both supervised and unsupervised techniques to leverage vast quantities of data. You should be passionate about building phenomenal products. Because you'll be working closely with researchers and engineers from a number of other teams at Apple, you're a standout colleague who thrives in a multifaceted environment with rapidly changing priorities.

Education & Experience

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

Additional Requirements

    • Solid understanding of both relational and NoSQL database technologies.
    • Experience with visualization, data mining, or statistical tools.
    • Experience with AB testing and data-driven product development.
    • Hands-on experience with ASR or NLP toolkits.
    • Working knowledge of iOS development.
  • Meeting any of the additional requirements is considered a plus.

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Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race,color,religion,sex,sexual orientation,gender identity,national origin,disability,Veteran status,or other legally protected characteristics. Learn more about your EEO rights as an applicant (Opens in a new window) .

Apple will not discriminate or retaliate against applicants who inquire about,disclose,or discuss their compensation or that of other applicants. United States Department of Labor. Learn more (Opens in a new window) .

Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in San Francisco,review the San Francisco Fair Chance Ordinance guidelines (opens in a new window) applicable in your area.

Apple participates in the E-Verify program in certain locations as required by law. Learn more about the E-Verify program (Opens in a new window) .

Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more (Opens in a new window) .

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