Posted:
8/11/2024, 5:00:00 PM
Location(s):
California, United States
Experience Level(s):
Mid Level ⋅ Senior
Field(s):
Software Engineering
NVIDIA is a learning machine that constantly evolves by seeking exciting opportunities that matter to the world, and that only we can solve. We attract the world’s best people, so we can achieve our highest aim: building a company that lets us do our life’s work, at the highest level of our craft. We are now seeking a Resiliency and Safety Architect to support the development of GPU (graphical processing units) and Tegra SoC hardware and software resiliency features. In this role, you will be a key member of a team of innovators, challenging the status quo and pushing beyond boundaries. You will have the opportunity to impact the industry's leading GPUs and SOCs powering product lines ranging from consumer graphics to self-driving cars and the growing field of artificial intelligence.
What you'll be doing:
Collaborate with the hardware and software teams to architect new resiliency and safety features and guide future development.
Optimize hardware and software features to improve system robustness, performance, and security.
Model and analyze RAS metrics like Failures in Time and Availability; and Safety metrics like Diagnostic Coverage and PMHF
Run simulations to analyze Architectural Vulnerability Factor and Liveness of on-die memory
Participate in testing new and existing resiliency and safety hardware and software features.
Develop diagnostics software components for Resiliency and Safety to run on NVIDIA GPUs.
Work on compliance of products with functional safety standards (ISO 26262 and ASPICE (Automotive SPICE)). This includes defining requirements, architecture, and design with end-to-end traceability, performing safety analyses - FMEA/DFA/FTA and ensuring compliance of software to MISRA and Cert-C standards.
What we need to see:
Master’s or PhD degree in Computer Science, Computer Engineering, Electrical Engineering or closely related degree or equivalent experience.
Familiarity with computer system architecture, microprocessors, and microcontroller fundamentals (caches, buses, direct memory access, etc.).
Basic knowledge of some aspects of GPU/SoC architecture - Clocks, Resets, Interrupts, Memory Controller, Multimedia accelerator pipelines.
Proficiency in C/C++.
Scripting and automation with Python or similar.
Understanding of the software development life cycle, from requirements to testing closure and maintenance,
Strong debugging and analytical skills.
Be self-driven and results oriented.
Ways to stand out from the crowd:
Familiarity with general HW concepts, Verilog RTL coding and simulations/debug.
Familiarity with GPU Architectures, Machine Learning/Deep Learning concepts
CUDA Programming
Experience in embedded software development.
Experience with resiliency and functional safety.
NVIDIA’s invention of the GPU 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company”. Do you love the challenge of crafting the highest-performance silicon possible? If so, we want to hear from you! Come, join our Accelerated and Resilient Compute Systems team and help build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field.
The base salary range is 120,000 USD - 230,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Website: https://www.nvidia.com/
Headquarter Location: Santa Clara, California, United States
Employee Count: 10001+
Year Founded: 1993
IPO Status: Public
Last Funding Type: Grant
Industries: Artificial Intelligence (AI) ⋅ GPU ⋅ Hardware ⋅ Software ⋅ Virtual Reality