Sr. Machine Learning Infrastructure Engineer, Creator Studio

At Apple, new ideas have a way of becoming phenomenal products, services, and customer experiences very quickly! The Creator Studio team needs your help shaping the next generation of creative editing tools by working on pioneering technologies to surprise and delight creative pros and enthusiasts alike. As a Machine Learning Infrastructure engineer, you will be working alongside world-class engineers and creatives to help innovate in the creative space in ways that only Apple can. This is a highly visible and impactful opportunity!

Description

In this role you will lead the development of scalable ML data infrastructure, enabling high-quality ML model development and continuous improvement of application features for creatives.

Minimum Qualifications

BS/MS in Computer Science or related field with 3+ years of relevant industry experience. Proficiency in a high-level programming language (preferably Python) and database query language (e.g., SQL). Strong understanding of software engineering best practices, especially around data modeling, schema design and building maintainable data access layers. Experience developing and optimizing large-scale ML workloads running on distributed processing frameworks. Strong understanding of an ML-based product lifecycle. Ability to communicate effectively and collaborate with partner teams, particularly ML research scientists and engineers. Ability to solve everyday problems in innovative ways. Committed to encouraging an open and inclusive work environment.

Preferred Qualifications

Working knowledge of modern database and distributed data processing technologies/frameworks (e.g., Spark, Dask, Ray, Presto, Parquet, Flink, Druid, Airflow, PostgreSQL). Experience with Python package management and build/deployment tooling (e.g., uv, poetry, hatch). Experience optimizing models and algorithms to run efficiently on resource-constrained platforms. Knowledge of cloud platforms and container orchestration technologies (e.g., Kubernetes, Docker, AWS, GCP). Familiarity with iOS ecosystem including the Swift programming language. Familiarity with model architectures and various training techniques, particularly in the Computer Vision domain. Familiarity with modern camera ISP and digital image processing algorithms and models. Knowledge and keen interest in learning the art and science of photography.