Machine Learning Engineer, Natural Language Generation (NLG) , Input Experience

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.

We are looking for a Machine Learning Engineer to develop the next generation of our ML models, so that they better serve the full range of our customers, across languages, writing styles, and other personal context, in a privacy-preserving way. You will build, run, and refine the training and evaluation pipelines that define our slice of Apple Intelligence, driving the focused experimentation and iteration that makes the user experience magical. You will join an ambitious, organized, and collaborative team. We're in a unique position to integrate the latest innovations from the ML community and work on features that reach everyday users, including your family and friends. You'll work closely with teams across Apple, collaborating on human interfaces, user studies, internationalization, ML technologies, system integration, and more.

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something-you'll add something. As a Machine Learning Engineer on our team, you will enable next-generation AI applications by building toolkits and workflows that scale to increasingly sophisticated modeling tasks. You will design the abstractions and implement the algorithms that facilitate efficient data synthesis, data curation, prompt engineering, and model evaluation. You will contribute to a company-wide effort to build robust modeling pipelines that optimize our ability to iterate rapidly and continuously deliver improvements to our customers. Finally, you will help define and refine new features that expand both the depth of Apple Intelligence's capabilities and the breadth of its support for the full spectrum of Apple customersDevelopment 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 changesMS or PhD in Computer Science or related field 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 statisticsFamiliarity 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