AIML - ML Engineer, ML Systems and Evaluation Engineering Client Tools and Frameworks

Apple - Cambridge, MA

Full-time

Cambridge, MA

Computer and Electronic Product Manufacturing

About the position

The ML Engineer position within the ML Systems Evaluation Engineering (MLSEE) team at Apple focuses on developing and evaluating machine learning systems and frameworks. The role involves owning requirements, developing proof of concepts, and contributing to the development roadmap for the ML system evaluation platform. The ideal candidate will have a strong background in software development, particularly in designing and optimizing large-scale data frameworks and APIs, and will play a key role in enhancing user experiences through innovative solutions.

Responsibilities

• Own requirements for the ML system evaluation platform, including proof of concept development.
• Co-own the development roadmap for ML system evaluation.
• Oversee system integration and contribute to software usage in evaluation plans.
• Build, measure, and leverage software to provide insights into platform changes.
• Drive innovative enhancements to Apple product user experiences.

Requirements

• BS/MS in Computer Science or related field.
• 5+ years of professional experience in software development with a focus on large-scale data frameworks and APIs.
• Strong software engineering skills including system design, development, testing, debugging, release, and maintenance.
• Proven expertise in Swift or Obj-C; Python and at least one other object-oriented programming language (e.g., C++, C#, Java) are desired.
• Good experience/exposure to service-oriented architecture.
• Knowledge of statistics-based evaluation approaches and ML training pipelines.

Nice-to-haves

• Experience delivering APIs/Frameworks used in production environments.
• Ability to develop long-term strategic visions and execute scalable solutions in agile environments.
• Strong organizational skills and experience working with multiple stakeholders.
• Excellent communication and documentation skills.
• Exposure to model development lifecycle including data preprocessing, model training, evaluation, deployment, and monitoring.

Benefits

• Equal opportunity employer committed to inclusion and diversity.