What are the responsibilities and job description for the Machine Learning Engineer - Vision Products Software position at Apple, Inc.?
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.\\nIn 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.\nYou'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.
Phd 3yrs or MS 5yrs relevant experience in related field (AIML, CS, EE etc.)\nStrong experience with deep learning, particularly in natural language processing and/or multimodal models\nHands-on experience with modern generative AI systems and computer vision models, including prompt design, fine-tuning, and evaluation\nFamiliarity with ranking, retrieval, and personalization algorithms\nProficiency in Python and experience with ML frameworks such as PyTorch (TensorFlow a plus)\nExperience integrating ML models into production systems\nStrong communication skills and the ability to collaborate across disciplines\nCuriosity, pragmatism, and a product-oriented mindset
Experience with conversational AI systems or interactive ML-driven experiences\nExposure to multimodal or embodied AI systems (voice, animation, agents, or real-time interaction)\nFamiliarity with Apple platforms, frameworks, or ML infrastructure\nEvaluation based measurement expertise using eval frameworks to measure non-deterministic experiences for consumer facing products
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.\nYou'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.
Phd 3yrs or MS 5yrs relevant experience in related field (AIML, CS, EE etc.)\nStrong experience with deep learning, particularly in natural language processing and/or multimodal models\nHands-on experience with modern generative AI systems and computer vision models, including prompt design, fine-tuning, and evaluation\nFamiliarity with ranking, retrieval, and personalization algorithms\nProficiency in Python and experience with ML frameworks such as PyTorch (TensorFlow a plus)\nExperience integrating ML models into production systems\nStrong communication skills and the ability to collaborate across disciplines\nCuriosity, pragmatism, and a product-oriented mindset
Experience with conversational AI systems or interactive ML-driven experiences\nExposure to multimodal or embodied AI systems (voice, animation, agents, or real-time interaction)\nFamiliarity with Apple platforms, frameworks, or ML infrastructure\nEvaluation based measurement expertise using eval frameworks to measure non-deterministic experiences for consumer facing products