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Ai Hardware Jobs (NOW HIRING)

Nvidia

AI Hardware Architect

Austin, TX · On-site

NVIDIA is hiring an AI Hardware Architect to analyze and architect the next generation of Artificial Intelligence hardware. We are looking for special individuals with a passion for delivering ...

Nvidia

AI Hardware Architect

Santa Clara, CA · On-site

NVIDIA is hiring an AI Hardware Architect to analyze and architect the next generation of Artificial Intelligence hardware. We are looking for special individuals with a passion for delivering ...

Nvidia

AI Hardware Architect

Santa Clara, CA

NVIDIA is hiring an AI Hardware Architect to analyze andarchitectthe next generation of Artificial Intelligence hardware. We are looking for special individuals with a passion for delivering ...

Nvidia

AI Hardware Architect

Austin, TX

NVIDIA is hiring an AI Hardware Architect to analyze andarchitectthe next generation of Artificial Intelligence hardware. We are looking for special individuals with a passion for delivering ...

Meta

Hardware Systems Engineer, NPI AI

Menlo Park, CA

$144K/yr

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 ...

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How much do ai hardware jobs pay per year?

As of Sep 4, 2026, the average yearly pay for ai hardware 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 is an AI hardware?

An AI Hardware job involves designing, developing, and optimizing computer hardware specifically for artificial intelligence applications. Professionals in this field work on specialized processors, accelerators, and memory systems to improve AI performance and efficiency. They collaborate with software engineers to ensure seamless integration between hardware and AI algorithms. Typical roles include AI chip designers, hardware architects, and FPGA engineers.

What are the typical day-to-day responsibilities of someone working in an AI hardware role?

Professionals in AI Hardware roles usually spend their days designing, developing, and testing specialized hardware components like processors, accelerators, and memory systems that support artificial intelligence workloads. Their work often involves collaborating closely with software engineers, data scientists, and system architects to optimize performance and ensure compatibility across platforms. They also participate in debugging, prototyping, and refining hardware based on simulation results, benchmarks, and real-world testing feedback. This combination of hands-on technical work and cross-functional collaboration creates a dynamic, results-oriented environment where innovation is highly valued.

What are the key skills and qualifications needed to thrive in the AI hardware position, and why are they important?

To succeed in AI Hardware roles, you should have a solid background in electrical engineering, computer engineering, or a related field, along with experience in hardware design and verification. Familiarity with tools like Verilog/VHDL, FPGA/ASIC development environments, and hardware simulation software is typically expected, and certifications such as a Professional Engineer (PE) license or specialized hardware design credentials can be advantageous. Strong problem-solving abilities, teamwork, and effective communication are essential soft skills for collaborating on complex, multi-disciplinary projects. These qualifications allow professionals to innovate and build efficient AI-optimized hardware systems that meet both performance and industry standards.

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ai hardware jobs near you
Infographic showing various Ai Hardware job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $146,230 per year, or $70.3 per hour.

AI Hardware Design Engineer

Siri InfoSolutions Inc

Santa Clara, CA • On-site

Contractor

Re-posted 28 days ago

Job description

Position:AI Hardware Design Engineer

Location: Santa Clara CA (ONSITE ROLE)

Duration: 6 Months

Local candidates preferred.

Skills: Digital : Python~Digital : Machine Learning Experience Required: 6-8

 We are seeking an Ai Hardware Design Engineer to join our team and drive innovation in AI-powered solutions. This role involves designing, developing, and optimizing generative AI models and workflows for applications such as content creation, product design, and intelligent automation.

  • Develop forward surrogate models for CVD/ALD/etch chambers mapping geometry, gas chemistry, flow, temperature, and power to film-uniformity, step-coverage, particle behavior, and thermal outcomes.
  • Implement inverse-design workflows where target performance specifications generate feasible chamber geometries, showerhead/baffle designs, and process conditions via generative or adjoint/topology-optimization methods.
  • Build bi-directional models that infer optimal process parameters for a given geometry and recommend geometry modifications when process latitude is insufficient.
  • Create high-fidelity digital twins combining physics-based solvers (CFD, plasma, heat transfer) with learned surrogate components for rapid design-space exploration.
  • Platform & MLOps Infrastructure: Implement and maintain robust, containerized MLOps systems (Docker, Kubernetes) in HPC environments to deploy models efficiently.
  • Develop robust multi-objective optimization and uncertainty-quantification workflows to ensure AI-generated designs are manufacturable, robust to variation, and compatible with downstream yield requirements.
  • Collaborate with physicists, domain experts, and software engineers to validate that AI models comply with fundamental scientific laws.

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.

Siri Infosolutions logo

About Siri Infosolutions

Sourced by ZipRecruiter

Our team of experts first gather each and every requirement of yours. Our research and development team then sit around those requirements and come up with a plan. Our implementation team then executes that plan for optimal results. After that our support team remains in constant touch with you during and after the entire process.

Industry

It services

Company size

201 - 500 Employees

Headquarters location

Edison, NJ, US

Year founded

2005

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