This role pays more than
90%
of similar roles. Most pay
$162,000–$235,750
— the shaded band above.
At the midpoint, this role pays about
$255k
versus about
$199k
for comparable roles.
Based on 240 similar postings.
Employer
About Apple Inc
Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software
Apple Inc currently has
1984 open roles
on FindRole.
Listed pay typically runs
$175,000–$277,600
across 1590 roles with salary data.
As a SW Optimization Engineer AI/ML within the Platform Architecture group, you will work to integrate hardware and software into a unified system while driving performance enhancements for Apple Silicon. You will analyze new and existing workloads to identify bottlenecks, provide recommendations for hardware and software improvements, and conduct performance studies to validate architecture decisions. Your daily work involves creating optimized implementations of machine learning workloads across the Neural Engine, GPU, and CPU, as well as developing performance models for emerging AI/ML techniques. To succeed, you must possess expertise in C/C++, Python, and PyTorch while utilizing knowledge of operating system internals and compiler technologies. You will build high-level complexity models and develop low-level performance libraries to solve complex computational challenges within the specific domain of AI/ML hardware acceleration and graphics processing.
Analyze new and existing workloads to identify performance bottlenecks in hardware and software.
Create optimized implementations of machine learning workloads on CPU, GPU, and Neural Engine.
Conduct performance studies to inform and validate architectural decisions.
Develop performance models for emerging AI/ML techniques and analyze system architecture trade-offs.
Deliver performance analysis instruments and optimized libraries for AI/ML applications.
Provide feedback to silicon and software teams based on identified patterns of performance challenges.
Prototype and benchmark algorithms across various hardware platforms to analyze performance metrics.
Develop high-level complexity models or low-level performance libraries for AI/ML accelerators.
What we're looking for
Bachelor's degree or equivalent experience in Computer Engineering, Computer Science, or a related field.
Experience in software development for AI/ML hardware accelerators, GPUs, image/video encoders, or similar.
Experience with AI/ML, graphics, or HPC performance benchmarks and workloads.
M.S. or Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or a closely related field (preferred).
10+ years of relevant experience in software performance optimization, analysis tools, and development of efficient computational algorithms (preferred).
Proficiency in C/C++ programming languages and scripting languages such as Python (preferred).
Knowledge of computer architecture fundamentals, operating system internals, and compiler technologies (preferred).
Proficiency in popular AI/ML frameworks like PyTorch and relevant software stacks (preferred).
Machine Learning
C++
Python
PyTorch
GPU
CPU
Neural Engine
SoC Architecture
Compiler
Simulation
System Architecture
Production Inference
Training Environments
System Power Modeling
AI Systems Architecture
C++
Python
Perl
Ruby
Power Analysis
Platform Management
Scripting
Debugging
Oscilloscopes
Logic Analyzers
Validation
Thermal Constraints