ML Safety Engineer
Apple - San Francisco, United States of America
Posted Apr 13, 2026
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 last checked Jun 13, 2026
- Salary
- Not verified not verified - source not recorded; timestamp not recorded
- 401(k) match
- Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.
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Market context
- Median wage (BLS OEWS)
- $111,944 national median
- Projected growth (BLS Employment Projections)
- +13.7% - Much faster than average
102% above the BLS national median 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
Application
- Cover letter
- Not verified
- Assessment
- Not verified
- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
ML Safety Engineer San Francisco, United States of America Apple Services Engineering (ASE) powers many AI features across App Store, Music, Video and more. We build deeply personal products with the goal of representing users around the globe authentically. We work continuously to avoid perpetuating systemic biases and maintain safe and trustworthy experiences across our AI tools and models. Our team, part of Apple Services Engineering, is looking for an ML Research Engineer to lead the design and continuous development of automated safety benchmarking methodologies. In this role, you will investigate how media-related agents behave, develop rigorous evaluation frameworks and techniques, and establish scientific standards for assessing risks they pose and safety performance. This role supports the development of scalable evaluation techniques that ensure our engineers have the right tools to assess candidate models and product features for responsible and safe performance. The capabilities you build will allow for the generation of benchmark datasets and evaluation methodologies for model and application outputs, at scale, to enable engineering teams to translate safety insights into actionable engineering and product improvements. This role blends deep technical expertise with strong analytical judgment to develop tools and capabilities for assessing and improving the behavior of advanced AI/ML models. You will work cross-functionally with Engineering and Project Managers, Product, and Governance teams to develop a suite of technologies to ensure that AI experiences are reliable, safe, and aligned with human expectations. The successful candidate will take a proactive approach to working independently and collaboratively on a
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