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Machine Learning Engineer - Vision Products Software

Apple - Los Angeles, United States of America

Posted Mar 31, 2026

Benefits

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401(k) match
Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.

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About this role

Machine Learning Engineer - Vision Products Software Los Angeles, United States of America AI is transforming how people interact with technology, and Apple is building the next generation of intelligent, privacy-preserving experiences across its platforms. We're looking for a Machine Learning Engineer to help prototype, build, and ship conversational and generative AI systems that feel deeply human, responsive, and trustworthy. In this role, you'll work at the intersection of machine learning research and product engineering-rapidly iterating on new ideas, translating them into scalable systems, and partnering closely with cross-functional teams to bring them to life. You'll contribute to foundational capabilities that power conversational understanding, generation, personalization, and embodied interactions for Apple's Vision devices As a Machine Learning Engineer on our team, you will design, prototype, and deploy ML-driven features that power conversational and generative experiences. You'll work hands-on with modern model architectures; ranging from large language and multimodal models to ranking and personalization system and integrate them into production frameworks used at scale. You'll collaborate closely with researchers, product managers, designers, and platform engineers to align on problem definitions, iterate on solutions, and ship features that meet Apple's standards for reliability, privacy, and delight. This role balances experimentation with execution: moving quickly when exploring new ideas, and rigorously when transitioning work into production. Design and implement ML models and algorithms for conversational understanding, generation, and personalization Rapidly prototype and evaluate new model architectures, prompting strategies, and fine-tuning approaches Translate research ideas into production-ready systems, collaborating across teams to ensure smooth

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