Graphics Software Engineer at Intel

Compensation

$128,880 – $181,940/yr

Location: Folsom, California
Type: Full-time

Description

Intel is seeking a Graphics Software Engineer to ensure the robustness and quality of their Graphics IP offerings. This role involves rigorous validation and debugging of graphics issues, integrating new features, triaging failures, analyzing cross-component features, developing debug tools, and improving functionality for content creation, gaming, and AI domains.

Required Skills

Quantitative Skills
Analytical Skills
Problem-Solving Skills
C Programming
C++ Programming
Python Programming
Validation
Debugging
CI/CD Automation
Windows OS Architecture
DirectX API
OpenGL API
OpenCL API
Vulkan API
TensorFlow Framework
PyTorch Framework

Additional Information

Minimum Education: Bachelor's degree in Computer Science, Computer Engineering or related field with 3+ years of relevant experience, or Master's degree in Computer Science, Computer Engineering, or Electrical Engineering with 1+ years of relevant experience.
Required Previous Experiences: Experience with computer graphics hardware and software and GPUs
Software development experience - C, C++, Python programming expertise and experience required
Validation, Debugging/Triage experience at the ingredient or platform level in one or more of the following domains: Graphics, Media, Display Technology
Experience with CI/CD and automating complex workflows.
Preferred Qualifications: Industry standard APIs and frameworks such as DirectX, OpenGL, OpenCL, Vulkan
Experience on latest Windows OS architecture
Framework and kernel debugging, Windows kernel internals
Debugging Windows Driver Model (WDM/WDF), Kernel Mode Driver
Understanding of media codecs and use-cases
Knowledge of device and system-level architecture, especially x86 based devices
Familiarity with various debug tools including Windbg, PIX, GPA, GPUView, emulators/JTAG-debuggers etc.
Understanding in state-of-the-art machine learning and deep learning algorithms, techniques and best practices, Expertise in Deep Learning Frameworks: TensorFlow, PyTorch.