Jobs / App***
On-device ML Infrastructure Engineer (Orchestration & Performance)
App*** · Cupertino, CA, United States
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Cupertino, CA, United StatesExp: 3-5 yrs150,400-277,600 USD/yearlyOnsite
Remuneration
150,400-277,600 USD/yearly
Location
Cupertino, CA, United States
Visa sponsorship
Sponsors visa
Job summary
The On-Device Machine Learning Infrastructure Engineer role focuses on developing the infrastructure necessary for efficient machine learning execution across App*** devices. Key responsibilities include implementing full-stack changes for deploying state-of-the-art models, collaborating with various teams for advanced applications, and optimizing model orchestration on App*** Silicon hardware.
Benefits
Comprehensive medical and dental coverageRetirement benefitsDiscounted products and free servicesReimbursement for educational expensesDiscretionary bonusesEquity
Qualifications
- Experience with MLIR-based compilers.
- Familiarity with deploying applications on App*** platforms.
- Knowledge of programming paradigms for GPU, CPU, and Neural Engine.
- Experience writing kernels for ML model execution.
- 3-5 years of experience with tooling in Python 3 and C++/Swift.
- Familiarity with common ML model architectures and execution schemes.
- Experience with PyTorch or related training frameworks.
Responsibilities
- Drive full-stack changes through the OS and tooling for deploying large SOTA models across the App*** Silicon ecosystem.
- Partner with teams to support advanced use cases for Siri, App*** Intelligence, Camera, and more.
- Make changes in the authoring and MLIR-based compiler for state-of-the-art model execution.
- Implement mechanisms for efficient orchestration of models across App*** Silicon hardware.
Skills
C++MakePython
Relocation
No