About the job
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.
Responsibilities
Building models for new user interface experiences.
Researching techniques to enhance model 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 requirements
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
Solid background in machine learning, data science, natural language processing, or statistics
Preferred
Experience 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