Our team is building next generation systems and tools supporting the research and development of machine learning models, and their integration into the products Apple customers love. We're a fast moving, highly skilled but small team designing and building a collection of tools and systems used by Apple’s MLEs and data scientists to build, test and deploy their products. Our systems have to scale, stay highly available, and "just work”. That's a tall order, and we're looking for talented and passionate engineers who love dealing with such challenges.

Description

Our team designs and builds ML systems and tools that support applied ML teams throughout their product development cycle. Using our systems, MLEs and data scientists perform data acquisition and synthesis, training, evaluation, and serving.

In this role, you will be responsible for engineering solutions to support model training, such as building reliable and scalable systems to run data processing pipelines, data generation engines, model evaluation infrastructure, and model inference systems. You may also be involved in directly integrating ML into products. You will need to rely on your creativity and problem solving to develop scalable, maintainable, and cost-effective solutions.

You will be successful and feel fulfilled in our team if you enjoy tackling challenging problems, have a strong sense of shared ownership, and thrive in a collaborative team setting.

Minimum Qualifications

• 5+ years industry experience as a Machine Learning Engineer or Software Engineer working on deploying large-scale systems
• Strong understanding in data centric systems, distributed systems, reliability, and cloud services
• Hands-on experience in designing and coding large scale systems
• Proven experience with applied machine learning, data engineering, or similar
• MS in Computer Science or related experience

Preferred Qualifications

• Experience with developer tools or developer productivity systems
• Experience with open source or inner source