We are seeking a highly skilled Senior Machine Learning Engineer specializing in Conversational AI to join our dynamic team. Our goal is to deliver offline evaluation insights that drive model development and improvements with wins for our end-user experience all while upholding the privacy standards that Apple is known for. The ideal candidate will play a pivotal role in the evaluation and enhancement of our Apple Intelligence products. You will collaborate closely with cross-functional teams to lead the creation and evolution of high quality datasets for evaluation of state-of-the-art models. With the advent of Apple Intelligence you will be facing novel challenges in developing representative datasets for delivering a highly personalized user experience. The key focus area of this role is to leverage large language models (LLMs) to automatically evaluate the impact of model changes on end-user experience as well as assess the quality and naturalness of conversations with a digital assistant. Additionally you will harness the power of generative AI to create adversarial scenarios that anticipate future user behaviors and edge cases enabling robust and forward-looking evaluation. These offline signals along with the generated datasets will be instrumental in shaping the future of Apple products ensuring that model improvements translate into tangible benefits for our users. These datasets and associated models power the next generation of Siri and Apple products and you will be part of this exciting journey.
7 years of professional work experience applying machine learning to real-world problems and crafting scalable and effective data solutions including demonstrated contributions towards the development of natural language products and/or technologies
Experience with managing datasets for ML training and/or evaluation
MS/PhD in Machine Learning Computer Science or equivalent experience in a related field
Excellent programming skills in Python
Good Conversational AI domain knowledge
Excellent problem solving critical thinking and communication skills
Expertise in defining and measuring evaluation coverage for large language models and agents
Enthusiasm and ability for continuing to learn new technologies
Experience with systems engineering; in-depth understanding of interdependencies of ML and SW components
Excellent understanding of an ML-based product lifecycle
Experience delivering large-scale cross-functional product or platform outcomes
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