AIML - Sr Backend Engineer, Data and ML Innovation
Apple - Seattle, United States of America
Posted Nov 5, 2025
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
- Not verified last checked Jun 13, 2026
- Salary
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- 401(k) match
- Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.
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Schedule
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
AIML - Sr Backend Engineer, Data and ML Innovation Seattle, United States of America Do you want to play a part in the next revolution in Foundation Models? Contribute to model hillclimbing for Apple Intelligence features that leverage Apple Foundation Models, and work with the people who built the intelligent products that helps millions of people get things done - just by asking or typing? The vision for the AI/ML FM Data organization is to improve Foundation Models by leveraging data from a variety of sources: crawl, license, vendor and internal crowd-sourcing. As a Sr Software Engineering on the team, you will drive backend innovations, identify key opportunity areas where data can play a crucial role and experiment with various data augmentation strategies to improve model training efficiency and performance.. We are looking for people with a track record in building scalable pipelines and services. Join us, and impact hundreds of millions of customers across billions of their interactions with foundation model powered Apple Intelligence features, that are available on iPhone, iPad, HomePod, Mac, Watch, CarPlay, and tv across more than 30 languages! As a Sr Backend Software engineer, you will be responsible for the following areas. - Training data pipeline development. Convert raw data into format acceptable by training jobs on GCP and AWS. Leverage internal and open-sourced training modules. - Large scale inferences: Leverage internal and open-sourced inference stack to generate inferences with fine-tuned LLMs on massive amounts of data, for pre-train and post-training - Data processing and
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