Machine Learning Engineer - Vision Products Software

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 integration Contribute to end-to-end ML pipelines, from data exploration and model training to deployment and evaluation Write clean, maintainable, and well-tested code that meets Apple’s production standards Participate in architecture discussions, design reviews, and peer code reviews Help shape technical direction and contribute to roadmaps for next-generation AI capabilities. Phd +3yrs or MS + 5yrs relevant experience in related field (AIML, CS, EE etc.) Strong experience with deep learning, particularly in natural language processing and/or multimodal models Hands-on experience with modern generative AI systems and computer vision models, including prompt design, fine-tuning, and evaluation Familiarity with ranking, retrieval, and personalization algorithms Proficiency in Python and experience with ML frameworks such as PyTorch (TensorFlow a plus) Experience integrating ML models into production systems Strong communication skills and the ability to collaborate across disciplines Curiosity, pragmatism, and a product-oriented mindset Experience with conversational AI systems or interactive ML-driven experiences Exposure to multimodal or embodied AI systems (voice, animation, agents, or real-time interaction) Familiarity with Apple platforms, frameworks, or ML infrastructure Evaluation based measurement expertise using eval frameworks to measure non-deterministic experiences for consumer facing products

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