Staff Applied Research and ML , Responsible AI and Safety

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Not verified checked Jun 13, 2026

Salary

$212K-$386K not verified - source not recorded

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

167% 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.

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

Company stage

Public-company Verified - from the job posting source checked Jun 20, 2026

Equity

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

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Staff Applied Research and ML , Responsible AI and Safety Cupertino, United States of America Play a part in building the next generation of generative AI applications at Apple. We're looking for AI Leaders, Scientists, Engineers and Researchers to tackle ambitious projects that will impact the future of Apple and our products. Research and advance red teaming methods for LLM's and diffusion models Research and develop mitigations and safeguards to ensure safe deployment of LLM's in Apple products Develop tools, metrics, and datasets for assessing and evaluating the safety of LLM's over the model deployment lifecycle, as well as methods and tools to help interpret and explain failures in language models Minimum Qualifications: PhD or equivalent experience, in Computer Science, or related technical field is helpful Demonstrated expertise in ML research and/or ML production deployment lifecycle Deep understanding of LLM Hands-on experience working with deep learning toolkits such as Tensorflow or PyTorch Ability to formulate a research problem, design, experiment, implement and communicate solutions Ability to work in a diverse collaborative environment Preferred Qualifications: Publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, EMNLP, etc.) Experience working on Responsible AI and AI Safety

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