ASIC Physical Design Intern - 2026 at NVIDIA

Shanghai, China

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Not SpecifiedCompensation

InternshipExperience Level

InternshipJob Type

UnknownVisa

Semiconductor, TechnologyIndustries

Requirements

Currently pursuing a Master's or PhD degree within a relevant or related field
Strong knowledge in IC design
Passionate about technology research and IC backend
Self-driven, good learning ability, good teamwork
Excellent communication skill, proficient in English reading and writing
Ways to stand out (Preferred)
Experience in IC backend implementation
Hands-on experience in EDA software from Synopsys (DC/PT/Formality), Cadence (RC compiler/LEC)
Proficient user of Python or TCL

Responsibilities

Chip integration and netlist generation, cross-team collaboration to implement chip partitioning and floorplan
Synthesis, RTL/netlist quality check, formal verification, function eco creation
Constraints creation and validation, timing budget, work with ASIC team to analyze/resolve function timing issues, achieve all special timing closure, such as io, test, clock, async etc
Work in conjunction with PR engineers for chip implementation to achieve full chip timing closure
Develop and improve entire timing closure flow from frontend (pre-layout) to backend (post-layout), flow automation development for above areas
Methodology in any of above areas

Skills

Key technologies and capabilities for this role

SynthesisFormal VerificationTiming ClosureFloorplanningNetlist GenerationConstraintsECORTLChip IntegrationChip PartitioningPlace and RouteAutomationPhysical Design

Questions & Answers

Common questions about this position

What degree is required for the ASIC Physical Design Intern position?

Candidates must be currently pursuing a Master's or PhD degree within a relevant or related field.

What are the key responsibilities for this intern role?

Responsibilities include chip integration and netlist generation, synthesis, formal verification, constraints creation and validation, timing closure, and developing timing closure flows and automation.

What skills make a candidate stand out for this position?

Experience in IC backend implementation, hands-on experience with EDA software from Synopsys (DC/PT/Formality) and Cadence (RC compiler/LEC), and proficiency in Python or TCL will help candidates stand out.

What is the work arrangement or location for this internship?

This information is not specified in the job description.

What qualities does NVIDIA look for in candidates?

NVIDIA seeks self-driven individuals with good learning ability, teamwork skills, excellent communication, proficiency in English, strong knowledge in IC design, and passion for technology research and IC backend. Creative and autonomous candidates are particularly encouraged to apply.

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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