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Internship Ai Hardware Jobs (NOW HIRING)

Unigen

Technical Marketing Engineer

Newark, CA · On-site

$100K - $125K/yr

Bachelor's degree in Computer Science, Computer Engineering, or related Engineering field required * 1-2 years of relevant experience with AI software and hardware technologies (multiple internships ...

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Etched

RTL Intern

San Jose, CA · On-site

... AI hardware experience; just the ability to learn quickly in a fast-paced, high-autonomy environment. We are looking for Fall '26, Spring '27, and Summer '27 interns. You may be a good fit if you ...

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Internship Ai Hardware information

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How much do internship ai hardware jobs pay per hour?

As of Jul 5, 2026, the average hourly pay for internship ai hardware in the United States is $17.44, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior AI researcher, machine learning director, or AI executive, often requiring advanced skills in deep learning, data science, and software engineering. These roles usually involve leadership responsibilities, extensive experience, and may include stock options or bonuses that contribute to the high total compensation.

Which 3 jobs will survive AI?

Jobs that require complex human interaction, creativity, and critical thinking, such as AI hardware engineers, data scientists, and cybersecurity specialists, are likely to persist as AI advances. These roles involve designing, managing, and securing AI systems, which demand specialized skills, problem-solving abilities, and adaptability that AI cannot fully replicate. Continuous learning and technical expertise in AI tools and hardware are essential for these positions.

What is the difference between Internship Ai Hardware vs Internship Data Scientist?

AspectInternship Ai HardwareInternship Data Scientist
Required SkillsHardware design, AI hardware acceleration, programming (C++, Python)Data analysis, machine learning, statistical skills, Python/R
Work EnvironmentHardware labs, R&D teams, manufacturing settingsData analysis teams, research labs, software environments
Industry UsageAI hardware development, semiconductor companies, tech firmsTech companies, finance, healthcare, research institutions

Internship Ai Hardware focuses on developing and testing AI hardware components, requiring hardware and embedded systems skills. In contrast, Internship Data Scientist emphasizes analyzing data and building models. Both roles are common in tech industries but differ in technical focus and work environment.

What are Internship AI Hardware positions?

Internship AI Hardware positions are temporary roles designed for students or recent graduates interested in working with the physical components and systems that support artificial intelligence technologies. Interns typically assist with designing, testing, and optimizing hardware such as processors, chips, and other devices that accelerate AI computations. These internships provide hands-on experience in areas like system architecture, circuit design, and hardware-software integration, often working alongside engineers and researchers. They are valuable opportunities to gain practical skills, industry exposure, and networking connections in the rapidly evolving field of AI hardware.

What kinds of projects do interns typically work on in an AI hardware internship?

As an AI hardware intern, you can expect to work on hands-on projects such as prototyping, benchmarking hardware accelerators, optimizing circuits for machine learning tasks, or supporting the design and verification of new AI chips. Interns often collaborate closely with experienced engineers and researchers, contributing to tasks like data collection, test automation, and performance analysis. These projects provide valuable exposure to real-world hardware development cycles and the unique challenges of deploying AI at scale.

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

To thrive as an AI Hardware Intern, you generally need a background in electrical engineering, computer engineering, or a related field, with strong knowledge of digital logic, computer architecture, and basic programming. Familiarity with hardware description languages (such as Verilog or VHDL), simulation tools, and lab equipment is typically required, and experience with platforms like FPGA or GPU accelerators is a plus. Strong analytical thinking, problem-solving abilities, and teamwork skills help you stand out in this role. These competencies are crucial for effectively contributing to hardware design and testing processes in fast-evolving AI hardware projects.

How much do AI interns get paid?

AI interns typically earn between $15 and $30 per hour, depending on the company, location, and level of experience. Paid internships often include opportunities to work with AI tools, hardware, and programming languages like Python or TensorFlow. Compensation can vary based on the internship's duration and whether it is full-time or part-time.
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Internship Ai Hardware jobs near you
Infographic showing various Internship Ai Hardware job openings in the United States as of June 2026, with employment types broken down into 40% Internship, 40% Full Time, 10% Part Time, and 10% Temporary. Highlights an 100% In-person job distribution, with an average salary of $36,265 per year, or $17.4 per hour.
Senior Research Scientist, AI Accelerator Design and VLSI

Senior Research Scientist, AI Accelerator Design and VLSI

Nvidia Corporation

Santa Clara, CA • On-site

$115K - $147K/yr

Full-time

Posted 25 days ago

Job description

We are now looking for a Senior Research Scientist!
NVIDIA is seeking a Senior Research Scientist to drive groundbreaking research at the intersection of AI HW/SW Co-Design, AI Hardware Accelerator Architecture, IC Design Methodology, and VLSI Design. Ideal candidates will have a broad perspective across areas including machine learning fundamentals, quantization and numerical methods for machine learning model optimization, digital VLSI circuits for computer arithmetic, high-productivity VLSI design and verification methodologies including applications of generative AI to hardware design, AI hardware micro-architecture, and VLSI methodology and implementation.
What you'll be doing:
  • AI Accelerator Hardware: Contribute to novel research advancing the state-of-the-art in AI accelerator design.
  • VLSI: Research creative and innovative ASIC and VLSI design techniques and/or novel digital VLSI circuits. Apply machine learning, generative AI, and state-of-the-art tools and methodologies to automated ASIC and VLSI design tool flows.
  • AI HW/SW Co-Design: Research and develop creative and innovative numerical methods for quantization, sparsity, or tensor decomposition grounded in computer arithmetic fundamentals and digital VLSI circuits.
  • Collaborate on the development of research prototype testchips.
  • Collaborate with AI researchers and hardware team members in research and product teams.
  • Publish and present your original research, speak at conferences and events

What we need to see:
  • PhD in Computer Science, Electrical/Computer Engineering, or related field (or equivalent experience), with 3+ years of post-PhD research experience and a strong record of impactful publications in top circuit, architecture, EDA, or AI/ML venues; with a proven ability to set research direction and translate ideas into tools or products.
  • Domain & Technical Expertise: Deep knowledge and 3+ years of post-PhD research experience in either VLSI (e.g., digital VLSI circuits and chip design methodologies), computer architecture, and/or numerical algorithms for AI model HW/SW co-design.
  • VLSI Implementation Skills: 5+ years of experience in hardware design with proficiency with modern EDA tool flows.
  • Programming & Systems Skills: 5+ years of experience in software tool development with proficiency in at least two of Python/PyTorch, C++, SystemVerilog, or CUDA.
  • Leadership & Collaboration: experience in leading research projects or teams, with a track record of mentoring junior scientists or interns, driving cross-functional initiatives with circuits/VLSI/architecture groups, and fostering collaborations with academia or industry.
  • Communication & Impact: Excellent written and verbal communication skills, with demonstrated experience presenting at top conferences; ability to influence both technical and non-technical audiences.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, autonomous and love a challenge, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 192,000 USD - 304,750 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until February 14, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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