Senior Staff Machine Learning Engineer, Apple Search & Knowledge Platforms

Apple is where individual imaginations gather together contributing to the values that lead to great work. Every The AI Search u0026 Knowledge Platforms team builds amazing products and services for Apples customers while serving as a foundational partner to teams across Apple. The team delivers world-class AI search and knowledge systems powering Siri Apple Intelligence Safari and iMessage and operates the foundational platforms and infrastructure that keep these intelligent experiences running at will lead the strong team of MLE SWE and data engineers responsible for delivering efficient and effective Generative AI models to build and improve the summarization capabilities across different data types.

In this role youll drive E2E Ru0026D 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.

8 years of experience in leading engineering/applied research/ML experiences in natural language processing SOTA generative AI modelsnProven record of consistent delivery of technology/products across the full Machine Learning life cyclenMS 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 engineering and Ru0026D 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 verbal and written communication skills to leadnExcellent product vision and sound business acumen. Ability to manage long-term strategy and short-term engineering leadership and fundamentals.