Architect - Performance Verification and Analysis at NVIDIA

Bengaluru, Karnataka, India

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Semiconductors, Artificial Intelligence, Automotive, High-Performance Computing, GraphicsIndustries

Requirements

BE/BTech or MS/MTech, or equivalent experience in relevant area, PhD is a plus
3+ years of relevant experience dealing with system level architecture and performance issues
Strong understanding of System-on-Chip (SoC) architecture, graphics pipeline, CPU architecture, memory subsystem architecture and Network-on-Chip (NoC)/Interconnect architecture
Solid programming (C/C++) and scripting (Bash/Perl/Python) skills. Exposure to Verilog/System Verilog, SystemC/TLM is a strong plus
Strong debugging and analysis (including data and statistical analysis) skills, including use of RTL dumps to debug failures
Exposure to performance simulators, cycle accurate/approximate models or emulators for pre-silicon performance analysis is a plus
Excellent communication and organization skills
Ability to work in a global team environment
Ways to stand out
Strong background in System Level Performance aspects for Graphics and High Performance Computing
Exposure to GPU application programming interfaces like CUDA, OpenGL, DirectX
Expertise in data analysis and visualization

Responsibilities

Performance analysis/bottleneck analysis of complex, high performance GPUs and System-on-Chips (SoCs)
Work on hardware models of different levels of extraction, including performance models, RTL test benches and emulators to find performance bottlenecks in the system
Work closely with the architecture and design teams to explore architecture trade-offs related to system performance, area, and power consumption
Understand key performance usecases for the product. Develop workloads and test suites targeting graphics, machine learning, automotive, video, compute vision applications running on these products
Drive methodologies for improving turnaround time, finding representative data-sets and enabling performance analysis early in the product development cycle
Develop required infrastructure including performance simulators, testbench components and analysis tools

Skills

GPU Architecture

SoC Architecture

Performance Analysis

Bottleneck Analysis

Hardware Modeling

RTL

Emulation

Performance Modeling

Machine Learning

Computer Vision

Performance Simulators

Testbenches

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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