Data Analytics and Applied AI Engineer- DFT Methodology 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 IntelligenceIndustries

Requirements

BSEE or MSEE from reputed institutions with 2+ years of experience in DFT, VLSI & Applied Machine Learning
Experience in Applied ML solutions for chip design problems
Significant experience in deploying generative AI solutions for engineering use cases
Good understanding of fundamental DFT & VLSI concepts - ATPG, scan, RTL & clocks design, STA, place-n-route and power
Experience in application of AI for EDA-related problem-solving (plus)
Excellent knowledge in using statistical tools for data analysis & insights
Strong programming and scripting skills in Perl, Python, C++ or TCL
Strong organization and time management skills to work in a fast-paced multi-task environment
Self-motivated, independent, ability to work independently with minimal day-to-day direction
Outstanding written and oral communication skills with the curiosity to work on rare challenges

Responsibilities

Explore Applied AI solutions for DFX and VLSI problem statements
Architect end-to-end generative AI solutions with a focus on LLMs, RAGs & Agentic AI workflows
Deploy predictive ML models for efficient Silicon Lifecycle Management of NVIDIA's chips
Collaborate closely with various VLSI & DFX teams to understand their language-related engineering challenges and design tailored solutions
Partner closely with cross-functional AI teams to provide feedback and contribute to the evolution of generative AI technologies
Work closely with DFX teams to integrate Agentic AI workflows into their applications and systems and stay abreast of the latest developments in language models and generative AI technologies
Define how data will be collected, stored, consumed and managed for next-generation AI use cases
Help mentor junior engineers on test designs and trade-offs including cost and quality

Skills

Applied AI

Generative AI

LLMs

RAG

Agentic AI

ML Models

DFT

DFX

VLSI

Silicon Lifecycle Management

Data Management

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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