AIML - Sr Data Scientist, Data and ML Innovation

Benefits

Parental leave

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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

$181K-$318K From the posting source checked Jun 20, 2026

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

123% 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 checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Equity

Offered Verified - SEC 10-K source checked Jun 20, 2026

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 - Sr Data Scientist, Data and ML Innovation Cupertino, United States of America We are a group of data scientists, partnering with ML researchers and engineers who develop foundation models that power Apple Intelligence features. We are pushing the boundaries of data science by developing novel techniques to evaluate the performance and capabilities of Foundational Models. In addition, we leverage data mining expertise to identify characteristics of training data that influence the performance of these models. If you are an accomplished data scientist, who wants to expand your influence in this fast evolving and exciting space of Generative AI, this is a great opportunity for you. As a Sr Data Scientist partnering with ML Researchers, you will bring your inquisitive mind and outstanding technical skills to unlock insights about the drivers that improve effectiveness of foundation models. Some projects that you are likely to drive are: - Assess existing foundation models evaluation techniques and improve them to suit Apple's use cases. - Studying loss patterns of models and attributing them to the drivers across the life cycle of model development from pre-training to SFT to RL. - Defining training data quality metrics and assessing quality of training data to ensure it positively impacts model performance. - Driving interpretability of ablation studies, documenting takeaways and driving a hypothesis driven experimentation strategy. - Building tools and automation process using LLMs to scale data science projects. Minimum Qualifications: 5+ years of data science experience demonstrating strong impact to product or model performance.

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