AIML - Machine Learning Research Scientist, Data and ML Innovation

Benefits

Parental leave

Not verified

Non-birth-parent leave

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Family-building benefits

• 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 checked Jun 13, 2026

Salary

$140K-$258K From the posting source

401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

78% above the BLS role benchmark for data and ml aggregate.

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source

Seniority

Mid From the posting source

Schedule

Shift type

Not verified

Weekend work

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Company

Equity

Offered Verified - SEC 10-K source

Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

AIML - Machine Learning Research Scientist, Data and ML Innovation Seattle, United States of America Would you like to join a team curious about understanding how foundation models work and to expand their capabilities in scientific domains? We perform and publish novel research and apply our findings to drive product directions. If you like designing clever approaches to understanding complex phenomena and using that knowledge to solve practical problems then this is the position for you. In this research scientist role you will join a small team of researchers performing fundamental research investigating foundation models for scientific domains. You will be involved in all aspects of performing research including project definition, method development, and experimental design. You will also run your own experiments, then analyze and interpret the results. You will take an active role in writing papers for publication and also using our findings to solve applied problems. You will also have the opportunity to collaborate with partner teams across Apple. Design robust experiments and methods to understand what foundation models do under the hood. Implement your methods and designs in experiment pipelines. Analyze and interpret your experimental results. Communicate results to teams across Apple. Write papers for publication in top-tier conferences/journals. Minimum Qualifications: PhD in computer science, statistics, physics, chemistry, electrical engineering, or operations research. Other hard sciences may also be considered. 3 publications in top-tier machine learning, statistics, or natural language processing venues. Deep knowledge of foundation models and experience training them and applying them to real,

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