Machine Learning Engineer • Mid-Level

Who you are

You have a Master's or PhD in Computer Science, Machine Learning, Statistics, or a related field, and at least 3 years of experience contributing to machine learning models in production environments. Your strong background in statistical analysis and modeling includes expertise in correlation analysis, clustering methods, probability theory, principal component analysis, outlier detection, and data visualization. You have hands-on experience improving large training datasets that consist of both structured and unstructured data, and you are adept at profiling and analyzing data to surface quality issues and identify gaps.

You are a detail-oriented professional who understands how data characteristics impact model performance. Your deep understanding of datasets drives informed decisions across the ML pipeline, ensuring the delivery of high-quality features to customers. You thrive in collaborative environments, working alongside creatives, designers, scientists, and engineers to innovate in the productivity space.

What you'll do

In this role, you will be responsible for profiling and analyzing data to surface quality issues and guide improvements to both evaluation and training datasets. You will work closely with the Productivity Apps team to shape the next generation of productivity tools, leveraging your expertise to enhance the performance of machine learning models. Your contributions will be critical to the success of the team, as you help innovate in ways that only Apple can.

You will also collaborate with cross-functional teams to ensure that the data used in machine learning models is of the highest quality. This involves identifying gaps in datasets and recommending improvements to enhance model training and evaluation processes. Your insights will directly influence the development of new features and functionalities in Apple's productivity applications.

What we offer

Apple offers a dynamic work environment where new ideas can quickly become phenomenal products and services. You will have the opportunity to work on pioneering technologies that surprise and delight users. The role is highly visible and impactful, allowing you to make significant contributions to the future of productivity tools. We encourage you to apply even if your experience doesn't match every requirement, as we value diverse perspectives and backgrounds.