Sr. Machine Learning Engineer, ML Systems Evaluation Engineering

Apple • Cupertino, CA

17h

About The Position

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.

Requirements

• 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

Nice To Haves

• 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

Responsibilities

• Curate and evolve high-quality evaluation datasets for state-of-the-art models.
• Collaborate with cross-functional teams.
• Deliver offline evaluation insights that drive model development and improve the end-user experience.
• Tackle novel challenges in evaluating highly personalized user experiences.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior