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Ai Hardware Engineer Jobs (NOW HIRING)

AI HARDWARE ENGINEER

Santa Clara, CA ยท On-site

$143K - $189K/yr

Ai Hardware Design Engineer Location: Santa Clara, CA Mode of Work: 5 days Onsite Required Skills & Qualifications * Education: Master s or Ph.D. in Computer Science, Computational/Electrical ...

To do this, we're building the world's first AI hardware engineer. Founded in 2019, our platform enables anyone to go from idea to manufacturable board using nothing more than a natural language ...

Electrical Hardware Engineer

Santa Clara, CA ยท On-site

$150K - $200K/yr

About us nEye.ai, a well-funded optical switch startup, is poised to revolutionize the future of ... Job Overview We are seeking an Electrical Hardware Engineer to join our hardware team and work ...

Electrical Hardware Engineer

Santa Clara, CA ยท On-site

$150K - $200K/yr

About us nEye.ai, a well-funded optical switch startup, is poised to revolutionize the future of ... Job Overview We are seeking an Electrical Hardware Engineer to join our hardware team and work ...

About us nEye.ai, a well-funded optical switch startup, is poised to revolutionize the future of ... Job Overview We are seeking an Electrical Hardware Engineer to join our hardware team and work ...

Hardware Systems Engineer, NPI AI Responsibilities: * Lead end-to-end system validation strategies for AI and HPC hardware platforms, including AI accelerators, GPU clusters, and high-bandwidth ...

Hardware Engineer

San Mateo, CA ยท On-site

$140K - $185K/yr

Physical AI is one of the most consequential technology shifts of our time, and Verkada is at the ... About this Role As a Hardware Engineer on our hardware team, you will lead the design and ...

Hardware Engineer

Blue Bell, PA ยท On-site

$110K - $120K/yr

Immediate need for a talented Hardware Engineer . This is a fulltime opportunity with long-term ... By applying to our jobs you agree to receive calls, AI-generated calls, text messages, or emails ...

Hardware Engineer

Sunnyvale, CA ยท Hybrid

$185K - $247K/yr

The Role We are seeking an experienced Hardware Engineer to join our Hardware team and play a key ... Experience designing hardware for AI/ML workloads or high-performance computing systems

Your work has the potential to shape the compute hardware and AI hardware going into our cutting-edge data centers affecting billions of users. Meta is seeking a motivated Power Engineer to join our ...

Develop AI model skills and recipes, and maintain multi-agent AI infrastructure. * Integrate AI ... hardware prototyping, systems integration, or lab engineering OR a relevant advanced degree + 3 ...

New

Head of Hardware

Palo Alto, CA

$145K - $191K/yr

We are seeking an experienced Head of Hardware to lead our hardware engineering efforts at an innovative AI startup revolutionizing chip design through machine learning. This pivotal leadership role ...

Hardware Engineer

San Francisco, CA ยท On-site

$170K - $190K/yr

Pano AI combines advanced hardware, software, and artificial intelligence into an easy-to-use, web ... Reporting to the Sr Manager of Hardware Engineering, you will be a key contributor to a small ...

Senior Hardware Engineer

Saratoga, CA ยท On-site

$210K - $265K/yr

Today's AI performance is frequently limited by communication bottlenecks. Eridu delivers multiple ... Visit our website eridu.ai to learn mo Position Overview As a Hardware Engineer in our Systems ...

This role sits at the center of cutting-edge AI hardware development, keeping the servers, PCIe systems, and engineering infrastructure running that power next-generation compute. You'll be hands-on ...

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Ai Hardware Engineer information

See salary details

$51K

$146.2K

$196.5K

How much do ai hardware engineer jobs pay per year?

As of Jul 12, 2026, the average yearly pay for ai hardware engineer in the United States is $146,230.00, according to ZipRecruiter salary data. Most workers in this role earn between $123,500.00 and $163,000.00 per year, depending on experience, location, and employer.

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

To thrive as an AI Hardware Engineer, you need strong foundations in computer engineering, digital logic design, and knowledge of machine learning algorithms, typically supported by a degree in electrical engineering or computer engineering. Familiarity with hardware description languages (such as Verilog or VHDL), FPGA/ASIC development tools, and experience with simulation and debugging systems are essential. Problem-solving abilities, attention to detail, and effective teamwork are standout soft skills for this role. These skills are crucial for creating efficient, reliable AI hardware solutions and collaborating across multidisciplinary teams to advance cutting-edge technologies.

What are AI Hardware Engineers?

AI Hardware Engineers are professionals who design, develop, and optimize computer hardware systems specifically for artificial intelligence applications. Their work involves creating specialized processors, such as GPUs, TPUs, or custom chips, that accelerate machine learning tasks and handle large-scale data processing efficiently. They collaborate with software engineers to ensure hardware and AI models work seamlessly together, improving performance, power efficiency, and scalability of AI systems. AI Hardware Engineers play a crucial role in advancing technologies used in data centers, autonomous vehicles, robotics, and edge devices.

What is the difference between Ai Hardware Engineer vs AI Software Engineer?

AspectAi Hardware EngineerAI Software Engineer
Required CredentialsBachelor's in Electrical Engineering, Computer Engineering, or related fields; knowledge of hardware design and programmingBachelor's or higher in Computer Science, Software Engineering, or related; proficiency in programming languages and AI frameworks
Work EnvironmentDesigning, testing, and developing AI hardware components in labs or manufacturing settingsDeveloping AI algorithms and applications in software development environments
Employer & Industry UsageTech companies, hardware manufacturers, research labsSoftware firms, tech startups, AI research organizations

While both roles focus on AI, Ai Hardware Engineers specialize in creating the physical components that enable AI systems, whereas AI Software Engineers develop the algorithms and software that run on hardware platforms. Understanding these differences helps job seekers target the right roles based on their skills and interests.

How do AI Hardware Engineers typically collaborate with software and data teams during the development process?

AI Hardware Engineers work closely with software developers and data scientists to ensure that hardware architectures are optimized for specific AI workloads. Collaboration often involves regular meetings to discuss performance requirements, compatibility challenges, and customizations needed for machine learning models. By maintaining open communication channels, hardware engineers can adapt designs based on feedback from software and data teams, ensuring seamless integration and optimal system performance.
More about Ai Hardware Engineer jobs
What cities are hiring for Ai Hardware Engineer jobs? Cities with the most Ai Hardware Engineer job openings:
What states have the most Ai Hardware Engineer jobs? States with the most job openings for Ai Hardware Engineer jobs include:
Infographic showing various Ai Hardware Engineer job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $146,230 per year, or $70.3 per hour.

AI HARDWARE ENGINEER

Ekcel Technologies Inc

Santa Clara, CA โ€ข On-site

$143K - $189K/yr

Other

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Job description

Role: Ai Hardware Design Engineer

Location: Santa Clara, CA

Mode of Work: 5 days Onsite

Required Skills & Qualifications

  • Education: Master s or Ph.D. in Computer Science, Computational/Electrical Engineering, AI/ML, or related field.
  • Technical Expertise:
    • Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow).
    • Experience with generative AI (LLMs, diffusion models, graph-based models).
    • Knowledge of computational materials methods (DFT, MD, phase-field modeling).
  • Additional Skills:
    • Familiarity with MLOps, HPC environments, and cloud deployment.
    • Proven experience (code repos, publications) bridging simulation software, hardware design, and ML.