Senior Machine Learning Engineer, NLP, Input Experience

Our team’s mission is to enhance ML powered user experiences on all Apple platforms through personalized multimodal input, composition, and understanding, with a global perspective. We achieve this daily by collaborating at the intersection of natural language processing, machine learning, and software engineering.

We are responsible for the machine learning and software (non-UI) development for several user-facing Apple Intelligence features, including Writing Tools, Summarization, Found In Apps, and Messages/Mail Smart Replies. Additionally, we oversee the keyboard machine learning and software stack, which includes autocorrection, suggestions, and inline completions.

If you’re passionate about being part of an ambitious, organized, and collaborative team that delivers user experiences with pioneering ML partnered with the best UI designs, join the Input Experience NLP team. Here, you’ll have the opportunity to transition from building groundbreaking NLP models to optimizing them for various hardware backends and user interfaces that create an enchanting experience. As a Machine Learning Research Engineer on our team, you’ll build and iteratively refine model pipelines that enable machine learning driven user experiences on Apple products. You’ll conduct experiments and create prototypes for innovative approaches to enhance the quality of our models and expand their intelligence. Additionally, you’ll implement the building blocks and infrastructure that integrate these innovations into our production pipelines and contribute evaluation metrics to measure progress.Building models for new user interface experiences. Researching techniques to enhance model

Machine Learning, Natural Language Processing (NLP), Software Engineering, Machine Learning, User Interface/Experience (UI/UX), Natural Language Processing (NLP), Apple, Keyboards, Data Science, Failure Analysis, behavior. Development and maintenance of scalable modeling pipelines that support multiple languages and production deployment. Defining robust automated evaluation metrics to facilitate model quality improvement through hillclimbing. Conducting failure analysis to identify and address the shortcomings of our models. Curation and synthesis of representative training and evaluation data. Implementation of experiments and simulations to assess the value of model modifications. Collaboration with language experts and QA to refine modeling approach in consideration of language-specific requirementsMS 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 Solid background in machine learning, data science, natural language processing, or statisticsExperience building and maintaining model pipelines end-to-end, from data curation to evaluation Ability to design and perform experiments that bring ML and NLP research ideas to production Familiarity with LLMs, such as SFT, RHLF, prompt engineering, data synthesis, automatic evaluation, and RAG Excellent written and verbal communication skills History of developing in Python and / or Swift Record of publications, innovations, and/or leadership