AI/ML - ML Performance Engineer, ML Platform & Technology
Santa Clara Valley (Cupertino), California, United States
Machine Learning and AI
The Core ML team in the AI / ML group at Apple is looking for an exceptional performance engineer to work on performance infrastructure (tools and benchmarks) to help identify bottlenecks and optimize our machine learning software stack. In this highly collaborative role, you will be at the center of multiple efforts to accelerate and optimize on-device machine learning. We are looking for someone that is familiar with machine learning, is passionate about identifying and optimizing performance bottlenecks. You should have a strong mix of education and practical experience with a real passion for diving in to challenging problems head first.
- Strong and proven software development skills
- Good understanding of machine learning fundamentals
- Proficiency in C/C++
- Experience with Swift, Objective-C and Apple development tools is a definite plus!
- Experience with Low level software and computer architecture.
- Passion for software architecture, APIs and high performance extensible software.
- Creative, collaborative, and product-focused
- Excellent communication skills
Work includes: Building and maintaining high performance machine learning frameworks that ship on all device classes. Ensuring high quality and agility with unit, integration and performance tests. You should possess strong skills in software design and programming and be passionate about developing new features, maintaining existing code, fixing bugs, and contributing to Apple's ML development tools strategy. Some familiarity with Low level software and computer architecture is expected.
Education & Experience
BS, MS or PhD in Computer Science with 4+ years experience
- Apple is an Equal Opportunity Employer that is committed to inclusion and diversity. We also take affirmative action to offer employment and advancement opportunities to all applicants, including minorities, women, protected veterans, and individuals