NVIDIA is a World Leader in AI Computing and Data Transportation Technologies, and we are now looking for an outstanding Software Automation Specialist to join our Quality Control Team in our Yokneam offices!
We are looking for a bright, innovative, and AI-driven engineer who is passionate about leveraging cutting-edge technologies to redefine software quality. The right candidate brings fresh thinking, a hands-on approach, and the ability to make things happen — independently. You'll challenge conventional processes and pioneer smarter, data-driven and automated approaches to quality, while collaborating with NVIDIA worldwide support teams, internal engineering and production groups, hardware teams, and Program Management groups.
What you'll be doing
Design and implement AI-powered quality processes and automation frameworks that go beyond traditional QA methods.
Build and maintain automations to streamline quality tracking, reporting, and alerting — from smart dashboards to automated reporting pipelines.
Leverage AI tools and large language models (LLMs) to accelerate root cause analysis, anomaly detection, and incident prediction.
Track and analyze customer quality incidents, applying AI-assisted techniques to identify patterns, resolve issues faster, and prevent reoccurrence.
Assist in driving software quality from concept to release delivery using data-driven KPIs and quality targets.
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Explore and introduce emerging AI methodologies to improve the quality mindset across engineering teams.
Contribute to quality process improvement initiatives and help maintain quality process documentation and records.
What we need to see
B.Sc. in Computer Science, Software Engineering, or another relevant technical degree.
2+ years of experience in software development, QA, or SW quality roles.
Hands-on experience with AI tools, LLMs, and automation workflows — especially Claude, web-building tools, and AI-assisted development environments.
Demonstrated ability to think creatively, challenge existing processes, and push things forward independently.
Outstanding interpersonal and communication skills — comfortable working with global teams and presenting ideas clearly across levels.
Strong analytical mindset with the ability to translate data into actionable quality insights.
Organized, independent, and able to juggle multiple workstreams.
Fluent English — written and spoken.
Ways to stand out from the crowd
Proven track record of using AI to automate or improve a quality or engineering process.
Experience building AI-assisted workflows, prompt engineering, or integrating LLM APIs.
Familiarity with Networking protocols and technologies.
Experience with Agile/DevOps methodologies.
Proficiency with BI tools and data visualization.
