Senior Design Engineer - Memory Subsystem
NVIDIA
NVIDIA
Join NVIDIA's elite team as a Senior Design Engineer, contributing to the cutting-edge memory subsystem components powering industry-leading GPUs and SOCs. This role offers a unique chance to make a significant impact within a dynamic, technology-driven company. Your work will influence product lines spanning consumer graphics, autonomous vehicles, and the rapidly expanding field of artificial intelligence. At NVIDIA, we are driven by a passion for parallel and visual computing, committed to transforming how graphics solve complex computational challenges. From simulating virtual worlds to powering AI, our GPUs are at the forefront of innovation.
As a Senior Design Engineer, you will drive critical aspects of the memory subsystem design. This includes owning the micro-architecture and RTL development for design modules, meticulously crafting features to meet stringent performance, power, and area targets. You will collaborate closely with hardware architects to define key features, partner with verification teams to ensure design correctness, and work alongside timing, VLSI, and physical design teams to guarantee timing closure and interface compliance. Additionally, you'll support FPGA and software teams for design prototyping and engage in post-silicon verification and debugging efforts.
We are looking for experienced engineers with a Bachelor's or Master's degree, or equivalent experience, and a minimum of 4 years in design. Essential qualifications include proven expertise in micro-architecture and RTL development for complex designs, and familiarity with design and verification tools (e.g., VCS, Debussy, GDB). A deep understanding of the complete ASIC design flow, from RTL design and verification through logic synthesis, prototyping, timing analysis, floor-planning, ECOs, and lab debug, is required. Proficiency in Verilog is a must. Experience with memory subsystem or network interconnect IP design, strong debugging and problem-solving skills, and scripting knowledge (Python/Perl/shell) are highly advantageous.
Nvidia
Semiconductors