Full-Time
AI Chip Design Engineer – New College Grad 2026
Posted on 7/4/2026
NVIDIA
10,001+ employees
Designs GPUs and AI HPC platforms
Compensation Overview
$116k - $218.5k/yr
Company Historically Provides H1B Sponsorship
Santa Clara, CA, USA
In Person
Master's, PhD
 Hardware Engineering (2) |
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- MS, PhD, or equivalent experience in Computer Science, Computer Engineering, Electrical Engineering, or Mathematics.
- Strong proficiency in agentic large language model libraries/ technologies such as LangChain, LangGraph, AutoGen, CrewAI, Retrieval-Augmented Generation, vector databases, prompt engineering, knowledge graphs, etc.
- Solid understanding of GPU/CPU architectures and designs.
- Strong analytical skills to solve complex problems.
- Knowledge of hardware verification methodologies and techniques.
- Hands-on experience with Verilog/SystemVerilog hardware description languages, temporal logic assertions, and the ability to quickly understand complex register-transfer level designs.
- Excellent command of scripting using Python.
- Excellent interpersonal skills, able to effectively collaborate and work with members of a distributed team.
- Play a key role in design, development and deployment of high performant agents’ frameworks and tools.
- Develop AI agents which can process large codebase and waves failures to help in coding and debugging tasks.
- Collaborate with hardware engineering teams to understand their specific needs and challenges and ensure our agent platform is well-suited to these needs.
- Develop and optimize retrieval and generation algorithms for enterprise data (text, code, and images) to build advanced AI applications.
- Stay ahead by engaging with the latest advancements in machine learning and AI to create state-of-the-art solutions.
- Integrate AI-driven optimizations into existing tools and flows.
- Lead with purpose and maintain high-quality engineering practices that inspire others to achieve excellence.
- Experience with distributed team collaboration and strong communication skills.
- Knowledge of NVIDIA hardware verification workflows and tooling (optional but preferred).
- Experience deploying AI agents in production environments and monitoring their performance and reliability.
NVIDIA designs and manufactures graphics processing units (GPUs) and computing platforms used for gaming, data centers, and artificial intelligence. These products work by using parallel processing to handle complex mathematical calculations much faster than standard computer processors, supported by a software ecosystem that allows developers to build and run AI models. Unlike competitors that may focus solely on hardware, NVIDIA integrates its chips with specialized software and cloud services to create a complete environment for high-performance tasks. The company’s goal is to provide the underlying technology necessary to power advanced computing, from realistic video game graphics to autonomous vehicles and large-scale data analysis.
Company Size
10,001+
Company Stage
IPO
Headquarters
Santa Clara, California
Founded
1993
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Simplify's Take
What believers are saying
- NVIDIA mobilized over $500 billion for AI infrastructure on August 10, 2026.
- NetSense pilot deployments start late 2026, creating new edge-AI revenue beyond data centers.
- Nemotron 3.5 Lightning targets inference, where Gartner says spending reaches $23.3 billion this year.
What critics are saying
- Six Wall Street partners concentrate NVIDIA demand into a credit-sensitive financing machine.
- Nemotron routing tools commoditize inference, inviting margin pressure from open models and rivals.
- If hyperscaler spending stalls in 2027, NVIDIA's order book and valuation reset fast.
What makes NVIDIA unique
- NVIDIA AI Aerial turned Verizon 5G into drone sensing with Lockheed Martin on August 12, 2026.
- Nemotron 3.5 Lightning and NeMo Switchyard bundle models, routing, and hardware into one stack.
- The August 10, 2026 financing platform makes NVIDIA compute an investable infrastructure asset.
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Growth & Insights and Company News
6 month growth
↑ 0%1 year growth
↓ -2%2 year growth
↓ -3%Verizon Communications has partnered with Lockheed Martin, Nvidia, Keysight Technologies, ODC and Astris AI to demonstrate drone-tracking technology using 5G networks. The system, called NetSense, was tested in Miami in July. NetSense combines Verizon's existing 5G spectrum with Nvidia's AI Aerial platform, ODC's AI-native Radio Access Network software, and Keysight's radio-frequency simulation technology. The system analyses radio-frequency disturbances to identify drones, predict flight paths and provide real-time alerts. The demonstration showed NetSense could detect and track drones without requiring changes to existing cellular infrastructure. The technology is designed for airports, power plants, stadiums, schools, hospitals and other critical infrastructure, as well as government monitoring. Separately, Morningstar named Verizon among its top 10 dividend stocks.
Intel's market value surged 474% over the past year to roughly $510 billion, whilst Nvidia's grew 24% to near $5.4 trillion. Intel's stock price rose approximately 400% from around $20 to about $101, with additional gains from share count increases of roughly one-sixth. Intel's share count grew from about 4.4 billion to over 5 billion shares, largely through stock issued to the US government under the CHIPS Act agreement. The company's revenue rose 25% year-over-year last quarter, its fastest growth in nearly 15 years, though it posted an $11.3 billion trailing-12-month loss. Nvidia generated $159.6 billion in trailing earnings, more than double the prior year, on $253 billion of revenue. Its price-to-earnings ratio now sits near 34.
Nvidia has released its open-source Nemotron 3.5 Lightning model, reinforcing CEO Jensen Huang's public support for open-source artificial intelligence. The move positions the chip maker opposite closed-model proponents like OpenAI and Anthropic in the AI development debate. The strategy serves Nvidia's commercial interests by directing enterprise spending towards hardware rather than expensive proprietary software. "What Nvidia is doing is removing that cost, which means [enterprise clients] have more money for hardware," said Bill Wong, AI research fellow at Info-Tech Research Group. Global AI inference spending is projected to reach $23.3 billion this year, surpassing training expenditure for the first time, according to Gartner. Nvidia holds 90% of the AI training market and has increased its inference market share from 66% to 74% year-on-year.
Nvidia has introduced NeMo Switchyard, a router designed to reduce enterprise AI costs by directing prompts to different models based on cost, latency, or quality requirements. The platform routes requests between expensive proprietary models and cheaper, smaller alternatives, potentially cutting job completion costs by 74% compared to using Claude Opus 4 alone, with approximately six-point accuracy trade-off. Switchyard functions as a proxy between inference servers and models, optimising which model handles each task. Nvidia suggests using smaller, specialised models for simple tasks like generating title cards, whilst reserving larger models for complex work. The company has developed application-specific models, including Nemotron Parse for PDF processing. Similar routing approaches have been adopted by OpenAI and AT&T. The telecommunications giant reportedly saved 80-90% in certain applications by switching to open-weight models, which now power 25% of its AI workloads.
Nvidia has partnered with major financial firms including Apollo, BlackRock, Blackstone, and Goldman Sachs to establish a $500 billion facility for AI data centre infrastructure. The initiative will focus on debt financing to provide computing access for Nvidia's largest customers. Nvidia reported quarterly revenue of $81 billion, up 85% year over year, putting its revenue run rate near $330 billion. The company projects $91 billion in revenue for the current quarter. Nvidia maintains financial relationships and ownership stakes in numerous AI companies including Anthropic, OpenAI, Intel, Coreweave, Nokia, Synopsys, and Marvell. The infrastructure partnership is expected to generate additional revenue for Nvidia, supporting its continued top-line growth of over 60% quarterly.