Performance and Modeling Engineer

Apple, Inc.; Austin (TX); On-site; USD 120,000 - 190,000; Full time

Job summary

APPLE INC in Austin, Texas, seeks a GPU performance engineer to work with driver, compiler and design teams to push GPU efficiency. You’ll validate features, quantify gains and develop tools for performance measurement across hardware and software domains.

The role centers on GPU microarchitecture analysis, RTL inspection, and scripting for regression testing, with a focus on delivering measurable improvements in mobile GPU performance.

Qualifications

• Bachelor’s degree in Electrical or Electronics engineering or related field with 1 year of experience.
• Experience using C and Python to develop performance analysis tools.
• Experience with compiler toolchains analyzing instruction scheduling, register allocation, and code generation.
• Experience using SystemVerilog/Verilog to read and debug RTL.
• Experience analyzing GPU microarchitecture with performance counters.
• Experience in memory hierarchy and NUMA analysis including caches and memory bandwidth.
• Experience with Python (Pandas, Matplotlib) for data visualization and dashboards.
• Scripting in Python and Shell to automate performance regression testing.
• Experience correlating compiler output to microarchitecture execution across silicon and pre-silicon.
• Experience with Git and collaborating on multi-engineer codebases.

Responsibilities

• Work with driver, compiler and design engineers to improve GPU performance.
• Validate functionality and quantify performance benefits of features and algorithms.
• Implement hardware and software solutions; conduct studies for performance challenges of mobile GPUs.
• Debug GPU performance issues with design engineers.
• Develop tools and models to measure and benchmark GPU performance.
• Collaborate with software teams to develop GPU models and performance dashboards.
• Conduct measurements, simulations and competitive analyses to drive improvements.

Skills

C language

Python

Shell scripting

GPU microarchitecture

Data visualization

Git

Education

Bachelor’s degree in Electrical/Electronics engineering

Tools

SystemVerilog/Verilog

RTL analysis

Compiler toolchains

Git

Pandas

Matplotlib

Job description

Imagine what you can do here. Apple is a place where extraordinary people gather to do their lives best work. Together we create products and experiences people once couldn't have imagined, and now, can't imagine living without. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do.

Description

APPLE INC has the following available in Austin, Texas. Working with driver, compiler and deigns engineers to improve GPU performance. Validating the functionality and quantify the performance benefit of the features and algorithms. Implementing in hardware and software; and conducting directed studies and help provide solutions to performance challenges unique to mobile GPUs that are aimed at driving the architecture of next generation mobile products via measurements, simulations, benchmarking, or competitive analysis. Debugging potential GPU performance issues and fix them with design engineers. Conducting GPU performance contents to measure GPU performance. Working with software teams to develop GPU model in different sections. Developing tools to aid in efficient measurement, communication and improvement of GPU performance. 40 hours/week.

Minimum Qualifications

• Bachelor’s degree or foreign equivalent in Electrical engineering, Electronics engineering or related field and 1 year of experience in the job offered or related occupation.
• Education and/or experience must include:
• Utilizing C and Python to develop performance analysis tools and automation scripts for GPU microarchitecture evaluation.
• Compiler toolchains, including experience analyzing instruction scheduling, register allocation, and code generation for GPU compute workloads.
• Utilizing SystemVerilog or Verilog, including experience reading and analyzing RTL to identify and debug hardware-level performance bottlenecks.
• Experience in GPU microarchitecture analysis, including utilizing performance counters to evaluate throughput, latency, and execution unit utilization.
• Experience in memory hierarchy and NUMA architecture analysis, including cache behavior, memory bandwidth characterization, and error correction mechanisms.
• Utilizing Python (Pandas, Matplotlib) and data visualization tools to build performance dashboards and report regression trends to engineering teams.
• Utilizing scripting languages including Python and Shell to automate performance regression testing, benchmark execution, and results collection.
• Experience in full-stack hardware/software performance analysis, including correlating compiler output to microarchitecture execution behavior across silicon and pre-silicon environments.
• Utilizing Git and code review processes, including experience collaborating on multi-engineer codebases to implement and validate performance improvements.

Preferred Qualifications

• N/A

This position is not subject to the application limits.

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