Intel
JR0288354 System Software Validation Engineer - Edge, Physical AI, and Robotics
$111K–$211K
US, Arizona, Phoenix · Full-time · Posted Oct 20, 2026
- Experience
- 2+ years in the specified software and automation areas; 1+ years in one or more of the specified Linux development areas. Experience may come from school work/classes/research, previous jobs, and/or internships.
- Education
- Bachelor's degree in Computer Engineering, Software Engineering, Electrical Engineering, Computer Science, or a related field.
About the job
Validates Intel system software by building test environments, creating and running validation plans, debugging failures, and improving automation and release quality.
What you'll do
- Design and develop validation environments, plans, and automated testing methods.
- Triage and debug software failures, analyze results, and recommend corrective actions.
- Maintain validation procedures and improve validation efficiency and quality.
What they ask for
- Bachelor's degree in Computer Engineering, Software Engineering, Electrical Engineering, Computer Science, or a related field.
- 2+ years of software development, integration, validation, and debugging across complex software systems; 1+ years in one or more specified Linux kernel, driver, or platform areas.
- 2+ years of experience in C and Python.
- 2+ years of experience in software debugging and performance analysis, and designing automated test frameworks, validation infrastructure, and continuous integration workflows.
Nice to have
- Familiarity with Intel architectures, GPUs, AI accelerators, system software, and platform technologies; understanding of LLMs, Transformer architectures, Generative AI, and model lifecycle management.
- Experience with PyTorch, TensorFlow, OpenVINO, ONNX Runtime, or OpenCV.
Pay
$111,030.00-211,200.00 USD (target compensation; pay type not specified)
Tools
Linux, C, Python, PyTorch, TensorFlow, OpenVINO, ONNX Runtime, OpenCV
AI focus
The role may involve validating software for AI platforms; preferred knowledge includes AI accelerators, LLMs, Transformer architectures, Generative AI, and model training, fine-tuning, optimization, and deployment.
Model-written summary · the original posting is authoritative