The Global Product Experience team creates groundbreaking user experiences across Siri markets using natural language processing (NLP) and machine learning (ML). The features we build are redefining how hundreds of millions of people across all Siri languages are connected to the information they are looking for and the apps they love to use through various devices! We work in one of the most exciting environments with pioneering ML and NLP models applied to production problems. We build ML technologies that scale to all Siri languages. You will have the opportunity to innovate with multilingual NLP models to help Siri understand different languages and user queries better!
We are responsible for the end-to-end user experience in all Siri markets. This means we build new features and scale them across Siri languages. As a Sr ML engineer in Global Siri, you will help us build ML solutions to scale new features, utterance understanding, and natural language generation faster in several languages. You should be comfortable working with large scale systems, write high quality code, and contribute to existing systems as well as developing new ones. Communication skills will be required to coordinate work across multiple teams.
Specific responsibilities include:
* Work on cutting-edge technology at the intersection of agents & multilinguality
* Understand how agentic LLMs learn capabilities across different languages
* Develop mechanisms to automate data creation and data filtering across different languages
* Find innovative solutions to scale fine-tuning approaches to multiple languages
* Devise automated approaches to evaluate the performance of agents across multiple languages
* Communicate and share your findings with the larger ML community and Global Siri teams at Apple
Qualifications:
* MS / PhD in Computer Science, Artificial Intelligence, Machine Learning or related field
* Experience with RAG, LLM Reasoning, and LLM Agent and/or Machine Translation
* Experience with or strong interest in agents, tool-use, planning, and multi-step reasoning
* Optionally experience with LLM reinforcement learning techniques
* Publication record in relevant conferences demonstrating ability to conduct innovative research in deep learning or a track record in applying deep learning techniques to products
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