We are looking for an excellent highly motivated Senior SW Engineer with experience in embedded software development to join the software testing team in the Data Processing Unit (DPU) SW Group. We are looking for a candidate with the ability to thrive in an environment with complex software and hardware designs, take ownership and lead the SW testing of key components of the DPU. The role includes working closely with HW, FW, and SW teams all over the world, and take our product to next level.
What you’ll be doing:
Build automated verification environment for high-end hardware and software which is at the forefront of innovation.
Develop and maintain test automation frameworks and scripts using Python.
Identify, analyze, and report software defects, inconsistencies, and other quality issues.
Make better product quality by improving tests coverage.
Take an active part in development, integration and verification with R&D.
Drive improvements for performance, quality, stability around SW acceleration solutions.
Stay up to date with industry best practices, new technologies, and emerging trends in software verification.
What we need to see:
Bachelor's degree in Computer Science, Software Engineering, or a related field (or equivalent work experience).
5+ years of experience in writing programs using Python.
Experience in developing modern Software testing System/QA automation and contribution with a real passion for automation.
Proved knowledge in performance testing scenarios and creation of performance reports.
Good background in designing, implementing, and debugging Software.
Background in Scripting (Bash, Groovy).
Expertise in networking & compute infrastructure (servers, switches, routers, TCP/UDP).
Knowledge of how to tune environment for the best performance and deploy infrastructure based on innovate technologies and high-end hardware.
Experience in Linux distributions (Centos/RedHat, Ubuntu, Fedora, SLES).
Extensive knowledge in Software debugging and problem solving skills.
Ways to stand out from the crowd:
Experience with PyTest or other testing tools.
Proficiency with data search and analytics engine (Elasticsearch, Kibana, Grafana).
Hands-on with virtualization in Linux (QEMU/KVM).
Work Background with CI/CD approach and toolset (Jenkins).
Knowledge of Docker and Kubernetes.
Understanding of C/C++ toolchain in Linux including cross-compilation (C, C++, automake/autoconf, cmake, meson).
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