About the job
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
Responsibilities
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.
Qualifications
Minimum
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
Preferred
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