Sr. Machine Learning Engineer, ML Systems Evaluation Engineering
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Join the team redefining what a deeply personal and integrated assistant can be.
As part of the Siri organization, you will help shape one of the world's most widely used AI assistants, powered by our next-generation of Apple Intelligence, with capabilities like personal context understanding and on-screen awareness, built with privacy from the ground up. Your work will have direct, meaningful impact for users across iOS, iPadOS, macOS, watchOS, and visionOS.
This is a rare opportunity to build at the intersection of cutting-edge AI and human-centered design, shipping technology that is centered around users and their needs.
Join the SCALE (Statistical Coverage and Large-scale Evaluation) team at Apple and contribute to a highly accomplished group that evaluates Siri and AI/ML models at scale to delight and inspire our users globally. If you are excited by large-scale systems, rigorous statistical evaluation, natural language understanding, and shaping the future of AI, we want you here! You’ll do more than join something, you’ll add something!
We are seeking a highly skilled Senior Machine Learning Engineer specializing in Conversational AI. Our goal is to deliver offline evaluation insights that drive model development and improve the end-user experience, all while upholding Apple's strict privacy standards.
In this pivotal role, you will collaborate with cross-functional teams to curate and evolve high-quality evaluation datasets for state-of-the-art models. With the advent of Apple Intelligence, you will tackle novel challenges in evaluating highly personalized user experiences.
7+ years of professional experience applying machine learning to real-world problems and crafting scalable data solutions, specifically in natural language products. Proven experience managing large-scale datasets for ML training and/or evaluation. Excellent programming skills in Python MS/PhD in Machine Learning, Computer Science, or equivalent experience in a related field
The qualifications that will benefit a candidate to be successful in your role. Please list no more than 6-8. Deep domain knowledge in Conversational AI and a strong understanding of the end-to-end ML product lifecycle.
Expertise in defining and measuring evaluation coverage for Large Language Models (LLMs) and agentic systems. Track record of delivering large-scale, cross-functional ML product or platform outcomes. Excellent problem-solving, critical thinking, and communication skills to drive alignment across teams.
Experience with systems engineering; in-depth understanding of interdependencies of ML and SW components