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Ai Chip Jobs (NOW HIRING)

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AI Automation Engineering Intern

San Jose, CA · On-site

$19.75 - $25.50/hr

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 ...

QCi

The role serves as a technical bridge between the research team developing novel quantum/AI architectures and the chip fabrication team responsible for implementation, ensuring that proposed designs ...

Cerebras Systems

Physical Design Engineer

Sunnyvale, CA · On-site

$230K - $280K/yr

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the ...

Silimate

Chip/Software Engineer

San Francisco, CA

Key Engineer Opportunity We're looking for a key engineer with significant experience with the VLSI front-end design flow and strong coding skills to help us build/scale chip AI models and agent ...

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Ai Chip information

What are some common challenges faced by professionals working in AI chip development, and how can they be addressed?

Professionals in AI chip development often encounter challenges such as balancing high computational performance with power efficiency, keeping up with rapid technological advancements, and integrating hardware with evolving AI algorithms. Collaboration between hardware engineers, software developers, and data scientists is essential to ensure that chips meet both performance and functional requirements. Staying current through ongoing learning and participating in cross-functional teams can help address these challenges and contribute to successful AI chip projects.

What are AI chips?

AI chips are specialized hardware components designed to accelerate artificial intelligence workloads, such as machine learning and deep learning tasks. Unlike traditional CPUs, AI chips are optimized for processing large volumes of data in parallel, making them highly efficient for neural network computations. These chips are commonly used in data centers, smartphones, autonomous vehicles, and edge devices to enable faster and more energy-efficient AI processing.

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 solid background in electrical engineering, computer architecture, and experience with hardware design, typically supported by a relevant degree. Familiarity with hardware description languages (such as Verilog or VHDL), EDA tools, and knowledge of semiconductor fabrication processes are crucial technical requirements. Attention to detail, strong problem-solving abilities, and effective teamwork skills help you excel in complex project environments. These competencies are vital for developing high-performance, efficient AI chips that power modern artificial intelligence applications.

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

AspectAi ChipAI Hardware Engineer
Required CredentialsBachelor's or higher in Electrical Engineering, Computer Engineering, or related fields; knowledge of VLSI designBachelor's or higher in Electrical Engineering, Computer Engineering, or related fields; experience with hardware design and testing
Work EnvironmentDesign labs, manufacturing facilities, R&D centersDesign labs, testing facilities, R&D centers
Employer & Industry UsageTech companies, semiconductor firms, AI hardware startupsTech companies, semiconductor companies, research institutions

While both roles involve hardware and AI technology, an Ai Chip focuses on designing and developing AI-specific chips, whereas an AI Hardware Engineer works on the broader hardware systems that support AI applications, including integration and testing.

More about Ai Chip jobs
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What job categories do people searching Ai Chip jobs look for? The top searched job categories for Ai Chip jobs are:
Ai Chip jobs near you
Infographic showing various Ai Chip job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution.
Senior Technical Program Manager - AI Infrastructure, Site Operations

Senior Technical Program Manager - AI Infrastructure, Site Operations

Cerebras Systems

Sunnyvale, CA • On-site

Full-time

Posted 7 days ago

Job description

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.
Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
About The Role
This Sr. TPM role owns site and data center operations programs supporting Cerebras' AI Cloud and customer deployments. The position sits at Sunnyvale HQ and works closely with Hardware Engineering, Inference Engineering, and Operations leadership to ensure Cerebras systems are reliably deployed, operated, and scaled.
This is a highly technical, execution-focused TPM role with strong emphasis on operational readiness, cross-functional coordination, and metrics/KPIs.
Responsibilities
  • Own end-to-end technical programs for data center and site operations
  • Act as single-threaded owner across:
    • Hardware & Systems Engineering
    • AI Cloud Infrastructure & Operations
    • Network & Storage Engineering
    • Facilities, power, cooling, and colo partners
  • Drive site readiness for Cerebras Wafer-Scale Engine systems
  • Partner on installation, commissioning, change management, and break/fix workflows
  • Lead incident reviews and postmortems; ensure corrective actions are closed
  • Define and own operational metrics and KPIs, including:
    • Availability and reliability
    • Incident rate, severity, MTTR / MTTD
    • Deployment readiness and time-to-service
    • Capacity and operational risk
  • Build executive-level dashboards and reporting
  • Establish program governance, risk tracking, and RACI clarity
  • Present program status, metrics, and operational risks to senior leadership
Required Background
  • 8+ years in Technical Program Management, Infrastructure Ops, or Data Center Ops
  • Experience leading large, cross-functional infrastructure programs
  • Strong understanding of:
    • Data center power and cooling fundamentals
    • Network and storage basics
    • Hardware-centric platforms
  • Proven ability to define and operationalize metrics
  • Strong written and executive-level communication skills
Preferred Experience
  • AI/ML, HPC, or accelerator-based infrastructure
  • High-density and/or liquid-cooled data centers
  • Working with colocation providers and facilities teams
  • Incident management, reliability, or service operations background

Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we've reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
  1. Build a breakthrough AI platform beyond the constraints of the GPU.
  2. Publish and open source their cutting-edge AI research.
  3. Work on one of the fastest AI supercomputers in the world.
  4. Enjoy job stability with startup vitality.
  5. Our simple, non-corporate work culture that respects individual beliefs.

Read our blog: Five Reasons to Join Cerebras in 2026.
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
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