AIML - Sr Machine Learning Engineer, Data and ML Innovation

The vision for DMLI organization is to improve Apple Foundation Model and advance in ML Research. Within this organization the mission of the ML Data & Applications (MLDA) team is to build products that enable Apple Foundation Model team to quickly identify model soft spots and iterate on improving model capabilities. As a UI Engineer on the team, you will work on an internal product that showcases the power of Apple Foundation Model and provides valuable data for model hillclimbing.

You will partner closely with Apple Foundation Model and SWE product feature teams to develop data visualization approaches for understanding complex aspects of the LLM user experience. You will build analytic, visualization, and other information products with a drive to automate and scale the insights available to science and engineering teams. You will guide best practices on the visual presentation of information and information architecture of LLM products. You will perform exploratory data analyses to enrich our mental models about LLM usage and identify new questions to pursue. We are looking for people with a track record in building front-end products and relationships to affect decisions. Join us, and impact hundreds of millions of customers across billions of their interactions with a personal, intelligent assistant who is available on iPhone, iPad, HomePod, Mac, Watch, CarPlay, and tv across more than 30 languages.

Have experience building front-end applications using Typescript, React and other UI frameworks.\nHave expertise in modern Javascript and data visualization libraries (e.g. D3, VisX, Vega). Data visualization skills are a plus.\nFamiliarity with API development using web frameworks (e.g., Express).\nExperience with testing frameworks (e.g. Jest, Mocha).\nHave familiarity with at least one backend programming language (e.g. Python) and are comfortable developing tools in a team environment (e.g. git, documentation, testing).

Think about data in terms of statistical distributions and have good instincts for how to find patterns and identify insights.\nHave good judgment for balancing art and science when visually communicating information.\nCan build information out of massive and complex datasets optimally (e.g. Hive, Spark SQL, Druid).\nAre self-motivated and curious with demonstrated creative and critical thinking capabilities and an innate drive to improve how things work.\nYou have a high tolerance for ambiguity. You find a way through. You anticipate. You connect and synthesize.\nYou have excellent verbal and written communications skills and experience in influencing decisions with information.