Company:
Job Area:
General Summary:
We are looking for a highly motivated Systems Test Engineer with 4+ years of hands-on experience in wireless networking product validation and functional testing. The ideal candidate should have strong expertise in Wi-Fi feature validation, troubleshooting, and test execution , along with a solid understanding of AI/ML applications running on edge devices .
This role requires strong analytical skills, experience working with embedded networking products, and mandatory proficiency in Python programming for test automation, log analysis, and test tool development.
Key Responsibilities
- Design, develop, and execute test plans and test cases for WLAN features and networking products.
- Perform functional, regression, interoperability, stability, and system-level testing of wireless solutions.
Validate WLAN features across Wi-Fi standards.
- Analyze logs, packet captures, and system traces to identify root causes of failures.
- Work closely with development teams to debug and resolve product issues.
- Develop and maintain Python-based test scripts, utilities, and automation frameworks.
- Validate AI/ML-enabled features running on embedded devices and edge platforms.
- Verify integration of AI applications with wireless networking functionality.
- Create detailed test reports, bug reports, and quality metrics.
- Participate in feature reviews and provide testability feedback during design phases.
Required Qualifications
- Bachelor's degree in Computer Science, Electronics, Telecommunications, or a related engineering field.
- Minimum 4 years of experience in WLAN QA, system testing, or wireless product validation.
- Wi-Fi protocols and standards
AI Application deployments
Hands-on experience with WLAN devices.
Strong debugging and troubleshooting skills.
Strong proficiency in Python.
- Test automation scripts
- Log parsing and analysis tools
Device management and monitoring scripts
- Familiarity with Python libraries for networking, automation, and data analysis.
AI on Embedded Devices
- Understanding of AI/ML applications deployed on embedded or edge-computing platforms.
Traffic Classification/Prioritization
Intelligent networking features
Parental Control
Edge AI inference applications
- Familiarity with AI deployment frameworks on embedded Linux platforms is desirable.
- Ability to evaluate performance impacts of AI workloads on networking functionality.
Preferred Qualifications
- Experience with Embedded Linux environments.
- Knowledge of container technologies and edge computing concepts.
- Familiarity with CI/CD pipelines and automated testing workflows.