ASIC Engineer at NVIDIA

Bengaluru, Karnataka, India

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Semiconductor, Artificial Intelligence, AutomotiveIndustries

Requirements

BTech/MTech with 2+ years of experience in micro-architecture and RTL development of complex designs
Strong digital design fundamentals
Deep understanding of ASIC design flow including RTL design, verification, logic synthesis, prototyping, DFT, timing analysis, floor planning, ECO, bring up, and lab debug
Experience in GPU/CPU/SoC performance verification and analysis
Experience with CPU, Memory controller, Bus Interconnect, Cache coherency
Experience in IP/SoC Design and Micro-architecture across High Speed IO controllers (UFS/PCIE/XUSB), Network on Chip

Responsibilities

Work on hardware models (performance models, RTL test benches, emulators) to find performance bottlenecks
Collaborate with architecture and design teams to explore trade-offs in system performance, area, and power
Understand key performance use cases; develop workloads and test suites for graphics, ML, automotive, video, computer vision
Make architectural trade-offs based on feature/performance/power; analyze implications, develop micro-architecture, implement RTL, drive verification, close timing, support silicon validation
Develop test plans, tests, and verification infrastructure for complex IPs/sub-systems/SoCs
Create verification environments using UVM methodology with reusable bus functional models, monitors, checkers, and scoreboards
Drive functional coverage-driven verification closure
Develop and enhance timing analysis/signoff workflows from pre-layout to post-layout at chip and block levels
Develop custom timing scripts using Tcl/PrimeTime for clock skew, clock dividers, core logic-IO interfaces (PCI-E, Frame-Buffer/Memory, HDMI, etc.)
Perform chip-level integration, physical partitioning, floor planning, physical verification, and EM/IR drop analysis
Design and implement test access mechanisms, IO BIST, memory BIST, and scan compression
Develop and deploy DFT methodologies for next-generation products
Innovate to improve DFT method quality
Work with architects, designers, and post-silicon teams

Skills

ASIC Design

RTL

Hardware Verification

Performance Modeling

Emulation

GPU

SoC

CPU

NOC Interconnect

High Speed IO

Memory Subsystems

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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