Implementation Methodology Engineer

Implementation Methodology Engineer at NVIDIA

NVIDIA has continuously reinvented itself over two decades, pioneering the GPU and revolutionizing modern computer graphics, parallel computing, and AI. As a learning machine, NVIDIA constantly evolves by adapting to new opportunities that are hard to pursue and matter to the world. Join us in our life’s work to amplify human creativity and intelligence.

We are looking for a highly motivated and self-starting Implementation Methodology Engineer to join the NVIDIA VLSI team. This challenging and exciting role involves collaborating to find solutions to complex technical problems.

What You’ll Be Doing

• Responsible for all aspects of front-end design implementation methodologies, including synthesis and formal-equivalence-checking.
• Drive flow automation and provide application support within the team.
• Utilize NVIDIA implementation flows and deep EDA tool expertise to enhance power, performance, and area (PPA) for NVIDIA's most critical designs.
• Collaborate closely with logic designers, physical designers, and EDA vendors to resolve challenging implementation issues and innovate new solutions.
• Provide essential support for EDA tools and associated flows.

What We Need To See

• BS or MS in Electrical Engineering, Computer Engineering, or a related field, or equivalent practical experience.
• At least 4 years of experience in logic design implementation and/or physical design implementation.
• A deep understanding of logic optimization techniques and their trade-offs concerning area, timing, and power.
• Strong understanding of physical design implementation concepts, including physical synthesis, placement, routing, and logic restructuring.
• Proficiency as a power user of synthesis and/or place and route EDA tools from major vendors like Synopsys (DC/FC) and Cadence (Genus/Innovus).
• Excellent debugging and problem-solving skills.
• Strong interpersonal skills, coupled with the ability to thrive in a dynamic team environment.

Ways To Stand Out From The Crowd

• Prior experience specifically in physical implementation.
• Demonstrated proficiency in scripting languages such as Python, Tcl, and Make.

NVIDIA is widely considered one of the technology world’s most desirable employers, known for its experienced and dedicated talent. If you are creative, autonomous, and driven by constant innovation to create industry-leading performance products, we encourage you to apply. Join the NVIDIA VLSI team and contribute to building real-time, cost-effective computing platforms that power Deep Learning and AI, Robotics and Autonomous Driving, Gaming, and High Performance Computing.

Key skills/competency

• VLSI
• GPU Design
• Synthesis
• Formal Verification
• EDA Tools
• Logic Optimization
• Physical Design
• PPA Optimization
• Python Scripting
• Problem Solving