Machine Learning Engineer - Visual Agents - Special Projects
Apple - Cupertino, United States of America
Posted Apr 17, 2026
Benefits
- Parental leave
- Not verified
- 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
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Where they hire
State eligibility is not yet verified.
About this role
Machine Learning Engineer - Visual Agents - 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 experiences powered by state-of-the-art agentic vision-language models that incorporate visual context into conversational interaction. We are looking for a Machine Learning Engineer to help us build, fine-tune, and rigorously evaluate these systems. A successful candidate has hands-on experience with vision-language models, knows how to translate ambiguous product requirements into measurable evaluation criteria, and is excited to work at the intersection of multimodal modeling and agentic AI. Build and evaluate vision-language agents that perceive real-world scenes and incorporate that context into conversational models Curate, annotate, and build multimodal datasets to support model training and evaluation Develop automated evaluation pipelines including LLM-as-judge frameworks, human evaluation protocols, and domain-specific benchmarks Fine-tune Large Language Models (LLMs) and Visual-Language Models (VLMs) to improve performance for specific use cases Work closely with other ML Researchers to define evaluation criteria and methodology to systematically evaluate foundation models Design controlled experiments to measure model capabilities,
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