CAD Software Student · NVIDIA

Mon, 27 Apr 2026 12:10:06 GMT
Engineering

NVIDIA · Yokneam

We are offering an enriching student position for a dedicated and driven Software Engineering student to join our team. This role is perfect for a student passionate about software engineering and interested in VLSI Backend CAD tools.

As part of our team, you will gain invaluable experience by learning from experienced engineers and contributing to the development of top-quality CAD tools and flows for our Backend team.

Responsibilities:

Support chip development teams by building software tools, automations, and AI-driven solutions that improve engineering productivity and design workflows. Contribute to the development of internal applications and flows across the full software lifecycle, including design, implementation, testing, deployment, and maintenance. Partner with engineers across DA and chip development teams to identify opportunities where AI can accelerate debugging, analysis, knowledge access, and workflow automation. Prototype and develop practical AI solutions such as copilots, intelligent assistants, and agent-based workflows that integrate with engineering tools and data sources. Collaborate with senior engineers to bring innovative ideas into production in a high-impact, fast-paced environment.

Requirements:

Pursuing a BS or MS in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field. Strong programming fundamentals, including object-oriented design and proficiency in Python. Strong analytical thinking, debugging, and problem-solving skills. Demonstrated interest in AI through hands-on projects, coursework, research, hackathons, or personal initiatives. Experience building practical AI applications using LLMs, agents, or workflow automation frameworks. Strong communication skills and the ability to work effectively in a collaborative team environment.

Nice to Have:

Hands-on experience building AI agents, copilots, or intelligent automation tools that solve real user problems. Experience integrating AI systems with APIs, databases, developer tools, or external services. Background in web applications, UI development, or building user-facing internal tools. Familiarity with data structures and algorithms, including graph-related concepts. Experience with Linux, SQL, and additional programming or scripting languages such as C++, Tcl, Perl, or Shell. Exposure to modern AI frameworks, evaluation methods, prompt design, or retrieval-based systems. Familiarity with VLSI, EDA workflows, or semiconductor development environments.