Full-Time
Test Engineer
Updated on 9/3/2026
NVIDIA
10,001+ employees
Designs GPUs and AI HPC platforms
No salary listed
Company Historically Provides H1B Sponsorship
Remote in USA
Remote
Bachelor's
 Manufacturing Quality & Test (1) |
|---|
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- Bachelor's degree in Electrical Engineering, Electronic Engineering, Mechanical Engineering, or a related field.
- 5+ years of experience in the semiconductor or electronics manufacturing industry.
- Strong background in ATC thermal solutions, as well as test hardware and software development is highly preferred.
- Proficiency in Linux shell scripting/Python/SQL, and AI tools for automation and data analysis.
- Strong troubleshooting and debugging skills in hardware, software, and manufacturing test environments.
- Experience with System-Level Test (SLT), New Product Introduction (NPI), high-volume manufacturing, or production test operations is preferred.
- Excellent analytical, problem-solving, and communication skills, with the ability to work effectively in a cross-functional environment.
- Hands-on experience with Allegro or similar schematic capture and PCB design tools is a plus.
- Hands-on experience with Creo or similar mechanical CAD software for engineering drawings and fixture design is a plus.
- Support all SLT NPI manufacturing and engineering activities in production floor, from product bring-up through mass production.
- Develop and improve automated test systems and thermal solutions for System-Level Testing (SLT).
- Perform test station setup, hardware configuration, qualification, and maintenance for NPI and production.
- Collaborate with cross-functional teams and vendors on the design, development, and validation of test equipment.
- Plan and execute Design of Experiments (DOE) to identify root causes and resolve production issues.
- Collect, analyze, and interpret manufacturing data to drive yield and productivity improvements.
- Provide frontline engineering support to production operations and troubleshoot test-related issues in real time.
- Develop and maintain test programs and tools for system-level and chip-level debugging, validation, and failure analysis.
- Leverage the latest AI technologies to improve testing efficiency, automate workflows, enhance data analysis, and drive quality improvements.
- Solid hardware and software development and debug skills
- Excellent analytical and problem-solving skills
- Strong knowledge of manufacturing processes and automation
- Demonstrated engineering expertise through hands-on experience
- Able to work under pressure in production environment
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
- Amazon ordered 2 million GPUs for 2027-2028, validating hyperscaler demand.
- August 2026 Lancium investment secured 4 GW leased capacity and 15 GW pipeline.
- Blackwell Ultra and Vera Rubin shipments began; production ships in late 2026.
What critics are saying
- Taiwan prosecutors indicted NVIDIA staff August 24, 2026 over illegal China server exports.
- China’s antitrust probe still threatens fines, remedies, and slower mainland sales.
- China export controls and ASIC substitution can cut NVIDIA off from a trillion-dollar market.
What makes NVIDIA unique
- CUDA and NVLink lock developers into NVIDIA’s full-stack AI platform.
- FY2026 revenue hit $215.9 billion, with data center revenue $193.7 billion.
- Rubin launched February 2026, targeting 10x lower inference costs than Blackwell.
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↓ -2%Nvidia CEO Jensen Huang declared that "AGI has arrived" whilst congratulating OpenAI on its newest model, Astra, released last Thursday. Astra was trained on Nvidia's chips and is described by OpenAI as the world's "most intelligent and aligned model". AGI, or artificial general intelligence, refers to AI systems that match or surpass human intelligence. OpenAI defines it as "highly autonomous systems that outperform humans at most economically valuable work". OpenAI president Greg Brockman said people will likely look back and think AGI was created "about this time". However, OpenAI CEO Sam Altman recently called AGI "a very poorly defined term" and "an irrelevant marketing term". Nvidia reported $96.2 billion in quarterly revenue in August, more than double the previous year, driven largely by demand for its AI chips.
NVIDIA CEO Jensen Huang claimed artificial general intelligence has arrived, citing OpenAI's latest ChatGPT model trained on his company's chips. NVIDIA now sells 72 chips in one box, wired to function as a unified system. Huang stated roughly 100,000 of these boxes trained OpenAI's new model, though he initially posted 300,000 before deleting and revising the figure without explanation. NVIDIA sold $89 billion of AI computers in three months, more than double the previous year. However, OpenAI has not confirmed AGI's arrival, and its president Greg Brockman stopped short of making such claims. A previously announced $100 billion partnership between the firms was never signed, and OpenAI has reportedly been buying fewer NVIDIA chips.
NVIDIA has taken a strategic investment in Lancium, a Blackstone-backed infrastructure company, to deploy its AI platform across power-ready data centres. The deal provides NVIDIA access to 4 gigawatts of leased capacity and a development pipeline exceeding 15 gigawatts. The partnership addresses a critical bottleneck in AI infrastructure, where compute demand has outpaced available power-ready capacity at gigawatt scale. NVIDIA's DSX MaxLPS technology enables up to 40% more GPU density within the same power budget, improving deployment economics. Lancium is backed by Blackstone Energy Transition Partners and Blackstone Multi-Asset Investing. The investment signals NVIDIA is moving beyond hardware sales to secure physical capacity for customers, recognising that compute demand requires corresponding power and space infrastructure. The arrangement allows NVIDIA customers faster access to large-scale infrastructure built specifically for demanding AI workloads.
AI stocks are predicted to remain strong investments over the next five years, with recent corporate guidance supporting this outlook. Broadcom reported 86% year-over-year revenue growth in its fiscal 2026 third quarter, with AI semiconductor revenue up 221%. The chipmaker projects AI chip revenue will double to $115 billion in fiscal 2027, then double again to $230 billion in fiscal 2028. Nvidia anticipates 70% year-over-year revenue growth in its fiscal 2028, citing supply chain issues as a limiting factor. Hyperscalers including Amazon, Microsoft, and Alphabet are generating substantial returns from their AI infrastructure investments through their cloud platforms. Investors are increasingly looking beyond chipmakers to smaller AI stocks for diversification opportunities.
Nvidia confirmed Thursday it will acquire AI model distribution platform Hugging Face for $12.9 billion. The company had reached $150 million in annualised revenue and raised nearly $395 million from investors including Amazon, Intel, Sequoia, and Coatue. The deal exemplifies how IPOs are becoming optional rather than obligatory for venture-backed companies. According to PitchBook research, the public offering is now "a tool for a specific problem" rather than an expected destination. Recent public market struggles support this shift. Chime went public at a steep markdown, whilst Figma has traded below its offer price for most of 2026. Only companies with capital needs too large for private buyers, such as OpenAI and Anthropic, now require public listings. Other successful exits include Stripe's acquisition of OpenRouter and SpaceX buying Cursor.