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Machine Learning Engineer

Yesterday Seattle, WA

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Description

APPLE INC has the following available in Seattle, Washington. Design machine learning models to run on consumer devices for understanding speech and text as part of an interactive real time dialogue system. Utilize data processing frameworks like Spark to pre-process datasets for training and evaluating ML models. Build end-to-end pipelines for automating data and modeling workflows, to achieve rapid prototyping and development of new models. Adopt the latest Cloud computing infrastructure into data and modeling pipelines. Adopt the latest neural architectures, such as DNN, RNN, LSTM, Transformer. Leverage speech recognition systems, text-based natural language models, and LLMs to generate data and signals for detecting a user's intent to interact with a device. Analyze production datasets to obtain actionable insights on how to improve model accuracy, through modification and augmentation of training data and/or model design. Combine all of these skills to deliver ML models for real-world features such as Hey Siri, Just Siri, Back-to-Back Requests, and Apple Intelligence. 40 hours/week. 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 $163,862 - $210,100/yr and your base pay will depend on your skills, qualifications, experience, and location. PAY & BENEFITS: 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. Learn more about Apple Benefits: https://www.apple.com/careers/us/benefits.html. Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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Minimum Qualifications

  • Master's degree or foreign equivalent in Computer Science, Electrical Engineering, Machine Learning, Computer Engineering, or related field and 3 years of work experience in the job offered or related occupation.
  • Education and/or experience must include:
  • Training speech-based and text-based ML models for interactive dialogue systems
  • Utilizing ML neural architectures including DNN, RNN, LSTM, or Transformer
  • Analyzing datasets and design ML training recipes to improve accuracy
  • Designing pipelines to synthesize ML training data with Large Language Model prompts
  • Designing and implementing end-to-end data and machine learning pipelines for training and deployment of ML models
  • Utilizing Python modules for machine learning
  • Utilizing Spark for large-scale data processing
  • Implementing automated deployment pipelines using Jenkins for CI/CD
  • Utilizing GitHub for source code management
  • Creating and presenting technical documentation

Preferred Qualifications

  • N/A

Apple 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 .

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Client-provided location(s): Seattle, WA
Job ID: apple-200617045-3337
Employment Type: OTHER
Posted: 2025-08-30T19:13:46

Perks and Benefits

  • Health and Wellness

    • Parental Benefits

      • Work Flexibility

        • Office Life and Perks

          • Vacation and Time Off

            • Financial and Retirement

              • Professional Development

                • Diversity and Inclusion

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