{
  "job_id": "g8kHORM2YYBKoKF9AAAAAA==",
  "job_city": "Cambridge",
  "job_state": "Massachusetts",
  "job_title": "Sr. Machine Learning Engineer, ASR Infrastructure and Tools, Siri Speech",
  "job_country": "US",
  "job_benefits": null,
  "job_latitude": 42.3666036,
  "job_location": "Cambridge, MA, United States",
  "job_onet_soc": "15111100",
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      "publisher": "Indeed",
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  "employer_name": "Apple",
  "job_is_remote": false,
  "job_longitude": -71.1056916,
  "job_posted_at": "18 days ago",
  "job_publisher": "Indeed",
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  "job_highlights": {
    "Benefits": [
      "Pay & Benefits",
      "At Apple, base pay is one part of our total compensation package and is determined within a range",
      "This provides the opportunity to progress as you grow and develop within a role",
      "The base pay range for this role is between $132,100 and $244,600, and your base pay will depend on your skills, qualifications, experience, and location",
      "Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs",
      "Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan",
      "You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition",
      "Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation",
      "Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program"
    ],
    "Qualifications": [
      "M.S. or Ph.D. degree in Computer Science, or equivalent experience",
      "Experience with optimizing and running large batch or training jobs on HPC-like clusters using GPUs or TPUs",
      "Strong data engineering background in speech and/or language/text/dialogue processing field",
      "Strong interpersonal skills to work well with engineering teams",
      "Excellent problem solving and critical thinking",
      "Ability to work in a fast-paced environment with rapidly changing priorities",
      "Passionate about building extraordinary products and experiences for our users",
      "Experience processing large, complex, unstructured data",
      "Knowledge of distributed data processing frameworks (Beam, Spark, Dask, Ray)",
      "Strong software engineering abilities, ideally Python"
    ],
    "Responsibilities": [
      "You will be part of a cross-functional team consisting of software engineers as well as data and machine learning engineers/scientists and having a large impact on the Siri product",
      "Work with open source tools like PySpark, Jax, Ray and others",
      "Optimize how to move multi-modal data from various sources into complex model training pipelines",
      "Use open source models to extract signals from large volumes of speech data to drive modeling improvements"
    ]
  },
  "job_max_salary": null,
  "job_min_salary": null,
  "job_description": "Want to join the team pushing the boundaries of AI and building an intelligent assistant that helps millions of people get things done? Join the Siri team at Apple! To build the best speech recognition models, we need to use the latest technology in distributed training and the best available data. We combine those needs into one team and are focused on blurring the lines between traditional “data processing” and “model training”. Efficiently training on petabytes of audio data pushes us to consider the entire training stack while developing new models to extract useful signals from unprecedented volumes of data.\n\nBy joining our team, you’ll have the opportunity to work with large and diverse datasets, iterate with research and production teams, and deliver voice based experiences to millions of users worldwide.\n\nDescription\n\nThe Siri Speech team is looking for exceptional individuals to extend the core technology that let Siri understand, learn, and remember. You will be part of a cross-functional team consisting of software engineers as well as data and machine learning engineers/scientists and having a large impact on the Siri product. This is a rare opportunity to apply distributed data engineering techniques at the intersection of various areas such as speech recognition, natural language processing, and dialogue management.\n\nIn this role you will\n• Work with open source tools like PySpark, Jax, Ray and others\n• Optimize how to move multi-modal data from various sources into complex model training pipelines\n• Use open source models to extract signals from large volumes of speech data to drive modeling improvements\n\nPreferred Qualifications\n\nM.S. or Ph.D. degree in Computer Science, or equivalent experience\n\nMachine Learning experience a plus\n\nExperience with optimizing and running large batch or training jobs on HPC-like clusters using GPUs or TPUs\n\nSpeech understanding or generation experience a plus\n\nStrong data engineering background in speech and/or language/text/dialogue processing field\n\nStrong interpersonal skills to work well with engineering teams\n\nExcellent problem solving and critical thinking\n\nAbility to work in a fast-paced environment with rapidly changing priorities\n\nPassionate about building extraordinary products and experiences for our users\n\nMinimum Qualifications\n\nExperience processing large, complex, unstructured data\n\nKnowledge of distributed data processing frameworks (Beam, Spark, Dask, Ray)\n\nStrong software engineering abilities, ideally Python\n\nApple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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 .\n\nPay & Benefits\n\nAt Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $132,100 and $244,600, and your base pay will depend on your skills, qualifications, experience, and location.\n\nApple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.\n\nNote: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.",
  "job_google_link": "https://www.google.com/search?ibp=htl;jobs&q&htidocid=g8kHORM2YYBKoKF9AAAAAA%3D%3D&hl=en-GB&shndl=37&shmd=H4sIAAAAAAAA_xWMMWoDMRBFSesjpPqNm7DsBkOapFpCCAa7iZLazGrHWgV5RmhkcOk7-FC5R04SpXnwivdWP3crcqXHnvwShbFjKhIl4E1Ccy4dRveBrRwLWS1nX8-FQTLjUzVZBxdLhMvMfsHv9YZvnWBt0lQF76oh8f3LUmu252EwS32wSjX63utpUOFJL0OL7B8HW6hwTlT5sHl6vPRZwsN6zDkxouCVTlOJc-AO-7HDl8TKM1zbsf0Bvt68hsoAAAA&shmds=v1_ATWGeeOVwQJRNWxRPDgtWYy4YHeK6eoTYhvT8lzihv_2SGftmQ&source=sh/x/job/li/m1/1#fpstate=tldetail&htivrt=jobs&htiq&htidocid=g8kHORM2YYBKoKF9AAAAAA%3D%3D",
  "employer_website": "https://www.apple.com",
  "job_onet_job_zone": "5",
  "job_salary_period": "YEAR",
  "job_apply_is_direct": false,
  "job_employment_type": "Full–time",
  "job_employment_types": [
    "FULLTIME"
  ],
  "job_posted_at_timestamp": 1773100800,
  "job_posted_at_datetime_utc": "2026-03-10T00:00:00.000Z"
}