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Ai Chips Jobs (NOW HIRING)

Advantest

AI Automation Engineering Intern

San Jose, CA

$19.75 - $25.50/hr

Why This Role Matters AI chips are pushing the boundaries of performance and complexity, and the engineering workflows that bring them to life must evolve just as fast. By embedding AI-driven ...

Advantest

AI Automation Engineering Intern

San Jose, CA · On-site

$19.75 - $25.50/hr

Why This Role Matters AI chips are pushing the boundaries of performance and complexity, and the engineering workflows that bring them to life must evolve just as fast. By embedding AI-driven ...

Conductor

ASIC Design Engineer

Boston, MA · On-site

$130 - $210/hr

Hands-on experience with ASIC design process for AI chips * Hands-on experience with multi-die/multi-chiplet/MCM designs #J-18808-Ljbffr

New

Conductor

ASIC Design Engineer

Austin, TX · On-site

$130 - $210/hr

Hands-on experience with ASIC design process for AI chips * Hands-on experience with multi-die/multi-chiplet/MCM designs #J-18808-Ljbffr

New

Etched

ASIC Timing Engineer

Cupertino, CA · On-site

$2.0K/mo

About Etched Etched is building AI chips that are hard-coded for individual model architectures. Our first product (Sohu) only supports transformers, but has an order of magnitude more throughput and ...

Etched

ASIC Timing Engineer

Cupertino, CA

$2.0K/mo

About Etched Etched is building AI chips that are hard-coded for individual model architectures. Our first product (Sohu) only supports transformers, but has an order of magnitude more throughput and ...

Etched

RTL Design Engineer

Cupertino, CA · On-site

$2.0K/mo

About Etched Etched is building AI chips that are hard-coded for individual model architectures. Our first product (Sohu) only supports transformers, but has an order of magnitude more throughput and ...

Etched

ASIC Timing Engineer

Cupertino, CA · On-site

$2.0K/mo

About Etched Etched is building AI chips that are hard-coded for individual model architectures. Our first product (Sohu) only supports transformers, but has an order of magnitude more throughput and ...

Conductor

Physical Design Engineer

Austin, TX · On-site

$130 - $170/hr

Experience with the physical design process for AI chips * Experience with the physical design process of analog and mixed signal blocks and macros #J-18808-Ljbffr

New

Conductor

Physical Design Engineer

Boston, MA · On-site

$130 - $170/hr

Experience with the physical design process for AI chips * Experience with the physical design process of analog and mixed signal blocks and macros #J-18808-Ljbffr

New

Nvidia

AI Hardware Architect

Santa Clara, CA · On-site

Together, we will build life-changing AI chips and chiplets for the rapidly growing AI infrastructure market. If you have knowledge of computer architecture, microarchitecture, and chip design, and ...

Etched

RTL Design Engineer

Cupertino, CA

$2.0K/mo

About Etched Etched is building AI chips that are hard-coded for individual model architectures. Our first product (Sohu) only supports transformers, but has an order of magnitude more throughput and ...

Nvidia

AI Hardware Architect

Austin, TX · On-site

Together, we will build life-changing AI chips and chiplets for the rapidly growing AI infrastructure market. If you have knowledge of computer architecture, microarchitecture, and chip design, and ...

Segment (Twilio)

AI Hardware Architect

Santa Clara, CA · On-site

$184 - $287.50/hr

Together, we will build life-changing AI chips and chiplets for the rapidly growing AI infrastructure market. If you have knowledge of computer architecture, microarchitecture, and chip design, and ...

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Ai Chips information

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How much do ai chips jobs pay per hour?

As of Aug 13, 2026, the average hourly pay for ai chips in the United States is $14.83, according to ZipRecruiter salary data. Most workers in this role earn between $10.82 and $15.38 per hour, depending on experience, location, and employer.

What are some common challenges faced by professionals working with AI chips, and how can they be addressed?

Working with AI chips often involves navigating rapidly evolving hardware architectures and keeping pace with new advancements. Professionals may face challenges related to optimizing software for specific chip designs, ensuring compatibility across platforms, and addressing power and thermal limitations. Collaboration with cross-functional teams—such as data scientists, hardware engineers, and software developers—is crucial to successfully integrate AI chips into products. Staying updated through continuous learning and leveraging available documentation and development tools can help mitigate these challenges.

What are AI chips?

AI chips are specialized hardware components designed to efficiently process artificial intelligence workloads, such as machine learning and deep learning tasks. Unlike traditional CPUs, AI chips (like GPUs, TPUs, and NPUs) are optimized for parallel processing and high-speed calculations required by AI algorithms. They help accelerate training and inference in applications ranging from speech recognition to autonomous vehicles. As AI technology advances, AI chips are becoming increasingly important in data centers, edge devices, and consumer electronics.

What are the key skills and qualifications needed to thrive as an AI chip engineer, and why are they important?

To thrive as an AI Chip Engineer, you need a strong background in electrical engineering, computer architecture, and semiconductor design, typically supported by a relevant degree. Proficiency with hardware description languages (such as Verilog or VHDL), EDA tools (like Cadence or Synopsys), and experience with high-level AI frameworks are commonly required. Strong problem-solving skills, attention to detail, and effective teamwork are critical soft skills for excelling in this role. These skills and qualities are essential to design high-performance, efficient AI chips that meet the complex demands of modern AI applications.

What is the difference between Ai Chips vs Data Scientists?

AspectAi ChipsData Scientists
Required CredentialsKnowledge of hardware design, electrical engineering, sometimes certifications in chip designDegree in data science, statistics, computer science; certifications like Certified Analytics Professional
Work EnvironmentHardware labs, R&D facilities, manufacturing plantsOffice settings, research labs, data analysis environments
Industry UsageTechnology, semiconductor manufacturing, AI hardware developmentTech companies, finance, healthcare, research institutions

Ai Chips focus on designing and developing specialized hardware for AI applications, requiring technical hardware skills. Data Scientists analyze data to extract insights, requiring statistical and programming expertise. While both roles are integral to AI development, they differ significantly in skills, environment, and industry focus.

Infographic showing various Ai Chips job openings in the United States as of August 2026, with employment types broken down into 5% Internship, 79% Full Time, and 16% Contract. Highlights an 95% In-person, and 5% Remote job distribution, with an average salary of $30,839 per year, or $14.8 per hour.

AI Automation Engineering Intern

Advantest

San Jose, CA

$19.75 - $25.50/hr

Full-time

Re-posted 19 days ago

Job description

About the Role

We are looking for a motivated and technically curious intern to join our Silicon Test Engineering team. In this role, you will leverage AI and modern automation tools to build intelligent workflows that accelerate the development, validation, and production testing of next-generation AI chips. This is a unique opportunity to work at the intersection of AI-driven software automation and cutting-edge silicon hardware.

What You Will Do

  • Design, develop, and deploy AI-powered automation workflows to streamline silicon test processes, from loadboard bring-up through high-volume production.
  • Use large language models (LLMs) and AI coding assistants to rapidly prototype scripts, data pipelines, and analysis tools that support test program development.
  • Automate repetitive engineering tasks such as test data extraction, result parsing, yield analysis, and report generation using AI-augmented toolchains.
  • Collaborate with test, design, and product engineers to identify manual bottlenecks and implement intelligent automation solutions.
  • Build and maintain dashboards or internal tools that provide real-time visibility into test metrics, yield trends, and program health.
  • Evaluate and integrate emerging AI tools and APIs into existing engineering workflows to improve team productivity.
  • Document processes, automation recipes, and best practices to enable team-wide adoption.

Why This Role Matters

AI chips are pushing the boundaries of performance and complexity, and the engineering workflows that bring them to life must evolve just as fast. By embedding AI-driven automation directly into our test and validation pipeline, you will help reduce time-to-market, improve yield, and enable the team to focus on high-value engineering challenges instead of repetitive manual tasks. Your work will have a tangible impact on products that power the future of artificial intelligence.

What You Will Gain

  • Hands-on experience applying AI to real-world semiconductor engineering problems.
  • Deep exposure to the full silicon lifecycle - from design validation through high-volume manufacturing.
  • Mentorship from experienced test and product engineers at the forefront of AI chip development.
  • A portfolio of automation projects you can showcase to future employers.
  • The opportunity to shape how a world-class engineering team integrates AI into daily operations.

What We Are Looking For

  • Currently pursuing a B.S. or M.S. in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
  • Strong programming skills in Python; familiarity with scripting, data manipulation (Pandas, NumPy), and API integration.
  • Demonstrated interest in or hands-on experience with AI/ML tools, LLMs, prompt engineering, or AI-assisted development (e.g., Claude, ChatGPT, Copilot).
  • Exposure to any of the following is a plus: semiconductor test (ATE), silicon validation, test program development, or hardware debug.
  • Ability to learn quickly, work independently, and communicate technical concepts clearly to cross-functional teams.
  • A builder's mindset - you see a manual process and immediately think about how to automate it.
  • Ability to work onsite at our San Jose, CA location five days per week. Relocation assistance is not provided to interns at this time.

Apply