Software Engineer, Chip Simulation at NVIDIA

Tel Aviv, Tel-Aviv District, Israel -

Full Time

Start Date

Immediate

Expiry Date

07 Oct, 26

Salary

0.0

Posted On

09 Jul, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, C, C++, Object-Oriented Design, Gdb, Linux, Docker, Inter-Process Communication, CI/CD, Hardware Simulation, Networking Protocols, Physical Layer Concepts

Industry

Computer Hardware Manufacturing

Description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA is looking for a phenomenal engineer to join the chip simulation team for networking chips and GPUs. This simulation platform enables NVIDIA engineers across firmware, SDK, and OS domains to develop and test their code without relying on physical hardware. If you're a creative, self-driven engineer passionate about systems-level design and eager to build technology that empowers internal teams, we want to hear from you. What You’ll Be Doing: Develop and maintain simulation components for the physical layer of NVIDIA’s high-performance networking chips (e.g., GPUs, switches, NVLink, Ethernet...). Collaborate with chip architects, firmware developers, and hardware design teams to accurately simulate complex physical-layer behaviors in software. Define, implement, and validate simulations of features such as link training, error injection, and transceiver behavior, making the simulation platform a go-to internal platform for development and debugging. Extend and optimize the simulation infrastructure by contributing to CI pipelines, automated test frameworks, and regression tools. Support internal users by debugging simulation flows and collaborating on bug resolution. Take part in future-facing innovation by enabling simulation for next-generation devices and features. What We Need To See: Bachelor's Degree or equivalent experience in Computer Science / Software Engineering / Computer Engineering / Electrical Engineering / Communication Engineering. 1+ years of experience in Python programming, with strong object-oriented design skills. Experience with C and/or C++, especially in systems or performance-sensitive environments. Experience debugging using debuggers (gdb), including concurrency issues (races, deadlocks...). Solid understanding of Linux, containerized environments (e.g., Docker), and command-line tools. Familiarity with Inter-Process Communication (IPC) mechanisms (sockets, message queues, shared memory...). Ability to communicate complex technical ideas in simple terms. Well-organized, proactive and capable of leading your own tasks. Collaborative personality with a love for teamwork. Ways to Stand Out from the Crowd: Experience building complex simulation or emulation systems, especially those simulating hardware behaviors. Experience with multi-platform systems spanning HW, FW, and SW. Experience with low-level networking protocols and applications. Knowledge of physical layer concepts. Experience contributing to CI/CD systems and tooling (e.g., Git, Jenkins, Gerrit). NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry. Learn more about NVIDIA.

Responsibilities

Develop and maintain simulation components for the physical layer of high-performance networking chips and GPUs. Collaborate with architects and firmware teams to implement features like link training and error injection while optimizing CI pipelines.