Data Scientist - Synthetic Data and ML Evaluations - Special Projects
Apple - Cupertino, United States of America
Posted Apr 17, 2026
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
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Data Scientist - Synthetic Data and ML Evaluations - Special Projects Cupertino, United States of America Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or experience we deliver is the result of us making each other's ideas stronger. The diversity of our people and their thinking inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something. The Special Projects team at Apple is developing novel user-facing conversational features that leverage the multimodal capabilities of state-of-the-art foundation models. A key component of this process is the ability to produce complex simulated scenario data, in order to train and evaluate agentic AI models. We are looking for a skilled Data Scientist to work closely with our Simulation and Machine Learning Evaluations teams to generate large synthetic datasets, analyze the gap between simulated and real data, and evaluate and fine-tune agentic AI model performance at various tasks. A successful candidate is experienced in managing large, multi-modal datasets, in translating subjective product requirements into objective criteria, and has strong statistical analysis skills. Work closely with ML Engineers to understand model evaluation needs Work closely with the Simulation team to design and generate large, multi-modal datasets for model evaluation Analyze the gap between simulated and real data Collaborate with the Simulation team to prioritize and
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