Machine Learning Engineer, Natural Language Understanding, Proactive

Location
Santa Clara
Workplace
On-site

About this role

Apple's On-Device Query Understanding team is building the next generation of personalized, intelligent search. You will research and develop novel approaches in query understanding and machine learning modeling, creating the technology that enables seamless search and assistant experiences across Apple products. This is a role for someone passionate about applying machine learning and generative AI to meaningful, large-scale challenges, where your work will directly shape how millions of people interact with Apple products every day.

Description


The On-Device Query Understanding team builds personalized, state-of-the-art query understanding models that power search intelligence across Spotlight and first-party apps like Mail, Photos, and Reminders. In this role, you will incorporate cutting-edge research in Large Language Models (LLMs), Natural Language Understanding (NLU), and machine learning inference optimization to deliver fast, power-efficient ML solutions to complex query understanding problems. You will bridge research and engineering excellence to drive scalable evaluations and on-device modeling improvements, directly impacting millions of Apple users while advancing how Apple understands what people are looking for, and why.

Minimum Qualifications


4 or more years of experience in machine learning, natural language processing, or computer vision, applied at scale Production software engineering experience with Python, Go, C/C++, Swift, or Objective-C Strong communication and collaboration skills Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Statistics, Physics, Mathematics, or a related field

Preferred Qualifications


Advanced degree (Master's or Ph.D.) in Computer Science, Statistics, or a related field, or equivalent industry experience Experience with Small Language Models (SLMs) and on-device LLM training, model compression/quantization, and deployment to production Experience in large-scale query understanding, search, recommendation, or personal assistant systems Proficiency with machine learning frameworks such as PyTorch, JAX, TensorFlow, or XGBoost Background in personalization and data-driven decision making, with the ability to prototype solutions and conduct critical analysis Experience with Swift, Swift frameworks, or Apple platform development is a plus Experience with build infrastructure, release management, and CI/CD pipelines is a plus

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