Drive E2E R&D and engineering to generate high-quality summaries and experiences for Apple users. This includes on-device LLM models for personal content summarization across 1P and 3P apps and powerful summarization models on Apples Private Cloud Compute addition improve the summarization models quality for world knowledge-seeking questions and Safari pages to provide accurate answers and highlight web page gists in real-time. Lead the team to develop SOTA LLM-based generative models groundedness models and safety models for accurate grounded concise and safe summaries. Develop sophisticated on-device and on-server software frameworks for context integration fast and cost-efficient LLM-based model inference. Integrate the Apple ecosystem with Apples LLM infrastructure and generative models to deliver delightful user experiences. Devise the product vision and strategy and execute the plan to deliver the highest quality end-user experience. Collaborate with various organizational partners to profoundly impact billions of Apple users worldwide.
5 years of experience in leading engineering/applied research/ML experiences in natural language processing SOTA generative AI models
Proven record of consistent delivery of technology/products across the full Machine Learning life cycle
MS or Ph.D. in Computer Science Machine Learning information retrieval data mining or a related field
Strong background and experience in Machine Learning NLP and RAG.
Strong engineering and R&D experience in LLM post-training advanced RL-based methods to improve LLM models safety and quality using RLHF/RLAIF reward model advanced RL policy optimization algorithms cutting-edge hallucination reduction methods and their engineering implementation hands-on experience to develop and ship RL based models with high availability low latency robustness and stability.
Exceptional verbal and written communication skills to lead
Excellent product vision and sound business acumen. Ability to manage long-term strategy and short-term deliverables.
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