GPU Machine Learning Developer Tools Engineer
Job Summary
Job Description
Apple's Graphics, Games, and Machine Learning Software team is seeking an engineer to develop Metal Developer Tools for debugging ML networks. This role involves creating new workflows and analysis tools for machine learning, graphics, and pro app developers to debug and optimize their networks for on-device inference across Apple Silicon SoCs. You will leverage computer architecture, operating system fundamentals, data structures, and algorithms to write efficient code for analyzing large models and designing intuitive visualizations to identify and resolve inaccuracies and performance bottlenecks. Collaboration with software and hardware teams is key to realizing the full capabilities of Apple's GPUs.
Must have:
- Technical BS/MS degree or equivalent experience
- Expertise in ML inference with frameworks like MPS Graph, CoreML, PyTorch, TensorFlow, Keras
- Excellent programming skills in UI frameworks like SwiftUI, UIKit, AppKit, Qt
Good to have:
- Expertise in Swift
- Experience designing intuitive UI/UX
- Experience developing on-device ML analysis and profiling tools
- Experience with GPU APIs like Metal, Direct3D, Vulkan, or OpenGL
- Expertise in GPU performance optimizations or GPU architecture
- C/C++ skills
Perks:
- Comprehensive medical and dental coverage
- Retirement benefits
- Discounted products
- Free services
- Reimbursement for certain educational expenses
- Discretionary restricted stock unit awards
- Employee Stock Purchase Plan
13 skills required
Job Details
Apple’s Graphics, Games, and Machine Learning Software team develops Metal, an API for GPU programming that allows efficient use of the GPU and minimizes CPU overhead. The Metal Developer Tools team is responsible for developing * Metal Debugger – a full featured GPU debugger and profiler, * Metal System Trace – a CPU and GPU runtime analysis tool for Metal, * MPS Graph viewer – a highly performant visualizer for ML networks. The Metal Developer Tools team is looking for an engineer who is excited to shape the future of developer tools for debugging ML networks. The ideal candidate will have a passion for creating the best possible visualizations and analysis tools for machine learning, and have a strong background in debugging and optimizing networks for on-device inference.
In this role, you'll be responsible for developing new workflows and analysis tools that help machine learning, graphics, and pro app developers debug and optimize their networks for on-device inference for the entire gamut of Apple Silicon SoCs. Building on a strong foundation of computer architecture and operating system fundamentals, data structure and algorithms, you'll write highly efficient code to analyze large models, then creatively design intuitive workflows and visualizations for finding and addressing numerical inaccuracies, performance bottlenecks or other issues. You will be working closely and collaboratively with partners across both software and hardware teams to fully realize the capabilities of Apple's best in class GPUs.
- Technical BS/MS degree / Equivalent Experience.
- Technical expertise in Machine Learning inference using frameworks such as MPS Graph, CoreML, PyTorch, TensorFlow, Keras etc.
- Excellent programming skills and UI frameworks such as SwiftUI, UIKit, AppKit, Qt etc.
- Technical expertise in Swift
- Experience with designing intuitive UI/UX
- Experience developing on-device ML analysis and profiling tools
- Experience with GPU APIs such as Metal, Direct3D, Vulkan or OpenGL
- Technical expertise in the area of GPU performance optimizations or GPU architecture
- Bonus points for C/C++
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.
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