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Ai Application Semiconductor Jobs (NOW HIRING)

Advantest

AI Application Engineer

Chandler, AZ · Hybrid

* This role sits at the intersection of semiconductor test engineering and AI, driving the ... As an AI Application Engineer, you will act as the bridge between semiconductor test engineering ...

Advantest

AI Application Engineer

Chandler, AZ · On-site

* This role sits at the intersection of semiconductor test engineering and AI, driving the ... As an AI Application Engineer, you will act as the bridge between semiconductor test engineering ...

Advantest

AI Application Engineer Intern

San Diego, CA · On-site

: Advantest, a leading Semiconductor Test and Measurement Company, is seeking self-driven and ... The internship involves working with the Application Engineering team developing AI toolsets to ...

Advantest

AI Application Engineer Intern

San Diego, CA · On-site

: Advantest, a leading Semiconductor Test and Measurement Company, is seeking self-driven and ... The internship involves working with the Application Engineering team developing AI toolsets to ...

Quest Global

AI/ML Engineer

Austin, TX · On-site

$95K - $105K/yr

... semiconductor industries. We are looking for humble geniuses, who believe that engineering has the ... AI application. Frameworks like LanGraph, CrewAI, or AutoGen. Ideal candidate has built a llm ...

Quest Global

AI/ML Engineer

Austin, TX

$95K - $105K/yr

... semiconductor industries. We are looking for humble geniuses, who believe that engineering has the ... AI application. Frameworks like LanGraph, CrewAI, or AutoGen. Ideal candidate has built a llm ...

Quest Global

AI/ML Engineer

Austin, TX · On-site

$95K - $105K/yr

... semiconductor industries. We are looking for humble geniuses, who believe that engineering has the ... AI application. Frameworks like LanGraph, CrewAI, or AutoGen. Ideal candidate has built a llm ...

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Ai Application Semiconductor information

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How much do ai application semiconductor jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for ai application semiconductor in the United States is $52.64, according to ZipRecruiter salary data. Most workers in this role earn between $42.31 and $60.58 per hour, depending on experience, location, and employer.

What are AI Application Semiconductors?

AI Application Semiconductors are specialized chips designed to accelerate the computation and processing tasks required by artificial intelligence (AI) applications. These semiconductors include processors like GPUs, TPUs, and custom AI chips that handle large-scale data operations and complex algorithms efficiently. They are commonly used in data centers, edge devices, smartphones, and autonomous systems to enable faster machine learning, deep learning, and inference tasks. As AI continues to evolve, demand for these semiconductors is increasing due to their role in powering everything from voice assistants to self-driving cars.

What are some common challenges faced by AI Application Engineers in the semiconductor industry, and how can they be addressed?

AI Application Engineers in the semiconductor sector often encounter challenges such as integrating AI algorithms with hardware, optimizing performance for specific chip architectures, and ensuring compatibility across diverse platforms. These professionals must work closely with hardware engineers, software developers, and data scientists to fine-tune solutions and address these complexities. Staying updated with the latest advancements in both AI and semiconductor technologies, as well as developing strong cross-functional communication skills, can help overcome these challenges and contribute to successful project outcomes.

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

To thrive as an AI Application Semiconductor Engineer, you need a strong background in electrical engineering, computer science, and semiconductor device physics, often supported by a relevant degree. Familiarity with hardware description languages (such as Verilog or VHDL), EDA tools, and experience with AI frameworks like TensorFlow or PyTorch are commonly required. Analytical thinking, problem-solving, and effective teamwork are crucial soft skills that help navigate complex projects and drive innovation. These skills and qualities are vital for developing efficient, cutting-edge semiconductor solutions that power advanced AI applications.
Infographic showing various Ai Application Semiconductor job openings in the United States as of May 2026, with employment types broken down into 80% Full Time, and 20% Nights. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $109,490 per year, or $52.6 per hour.

AI Application Engineer

Advantest

Chandler, AZ • Hybrid

Full-time

Posted 23 days ago

Job description

Job Description

  • This role sits at the intersection of semiconductor test engineering and AI, driving the transformation of traditional test workflows into AI-powered systems.
  • As a member of the US AI R&D team, you will work closely with 93K R&D engineers, AI engineers, and data scientists to define, develop, and deploy next-generation AI capabilities for the V93000 platform.
  • As an AI Application Engineer, you will act as the bridge between semiconductor test engineering workflows and AI systems, enabling step-change improvements in productivity such as:
    • test program generation
    • debug and root cause analysis
    • knowledge-driven engineering workflows
  • You will lead customer engagements for AI solutions, serving as the primary interface for:
    • use case discovery
    • product definition
    • feedback and iterative improvement
    • rollout and adoption of new capabilities
  • You will collaborate with global R&D teams to influence product direction and strategy for AI-enabled test solutions.
  • You will design and execute pre-sales and proof-of-concept activities, including:
    • customer demos
    • benchmark studies
    • pilot deployments
  • You will stay current with advances in AI/ML (e.g., LLMs, RAG, agent workflows) and drive internal and external enablement through workshops and training.

Technical Environment

You will work in a hybrid environment combining:

  • Linux-based systems (e.g., Red Hat Enterprise Linux)
  • V93000 / SmarTest development ecosystem
  • Modern AI-assisted development workflows, including:
    • AI-enabled IDEs such as VS-Code, Cursor, GitHub Copilot, and Visual Studio Code
    • Markdown-driven prompt and agent design
    • Python-based automation and AI tooling
  • API-driven systems, version control (Git), and integration with AI platforms and services

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