Machine Learning Engineer - Natural Language Generation, Input Experience

Apple
Seattle, United States of America2026-04-30

About the job

From our origins in iPhone keyboard input, the Input Experience NLP team has expanded to a broad charter: improve the user experience with robust language understanding and personalized text composition, across languages and Apple platforms. We build the ML models that underlie Summarization, Smart Reply, Writing Tools, and other features deeply integrated into Apple products. Generative AI is a transformative technology that we have only just begun to incorporate into our digital lives, to help everyday people digest the deluge of information they receive and express themselves more clearly. On our team, you will help build the future and have a voice in the shape it takes.

Responsibilities

Development and maintenance of data and model pipelines that scale to deployment in production

Building toolkits for iterating on model quality via data synthesis and prompt engineering

Definition of robust automated evaluation mechanisms to facilitate hillclimbing on model quality

Failure analysis from user feedback to understand shortcomings of our models and evaluation data

Research into state-of-the-art techniques for improving model quality and robustness

Implementation of experiments and simulations to assess the value of model changes

Qualifications

Minimum

MS or PhD in Computer Science or related field with at least 2 years of industry experience

Strong Python programming skills, with experience developing production-quality Python modules

Experience building and maintaining model pipelines end-to-end, from data curation to evaluation

Solid background in machine learning, data science, natural language processing, or statistics

Preferred

Familiarity with LLMs, such as SFT, RHLF, prompt engineering, data synthesis, automatic evaluation, and RAG

Expertise in MLOps and a passion for software quality, based on CI/CD principles

Excellent written and verbal communication skills

Background in linguistics, fluency in multiple languages, or a passion for scaling NLP features for global audiences

History of developing Python packages and supporting users and other teams