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Ai Chip Jobs (NOW HIRING)

FuriosaAI, Inc.

Solution Architect - US

San Francisco, CA · On-site

$110 - $150/hr

Prior experience at a US AI chip company, cloud silicon team, or AI infrastructure startup * Familiarity with NPU/GPU accelerator ecosystems, PCIe integration, and data center hardware deployment

Cerebras

Senior Performance Engineer, Inference

Sunnyvale, CA · On-site

$122K - $167K/yr

Cerebras Systems builds the world's largest AI chip, transforming the user experience of AI applications. They are seeking a Senior Performance Engineer to focus on performance benchmarking and ...

Bronco AI

Founding AI Engineer

San Francisco, CA · On-site

Bronco AI is focused on advancing chip development through AI agents that enhance chip verification and design processes. The Founding AI Engineer will be responsible for developing the core ...

Etched

Technical Program Manager, Infrastructure

San Jose, CA · On-site

$151K - $195K/yr

Etched is an AI chip startup that designs and manufactures hardware systems optimized for artificial intelligence model inference workloads. Founded in 2022, the company is headquartered in San Jose ...

Etched

Machine Learning Research Engineer

Cupertino, CA · On-site

$252K/yr

Etched is an AI chip startup that designs and manufactures hardware systems optimized for artificial intelligence model inference workloads. Founded in 2022, the company is headquartered in San Jose ...

Astera Labs

Chip Lead, Senior Director

San Jose, CA · On-site

ALAB) provides rack-scale AI infrastructure through purpose-built connectivity solutions. By ... Drive chip development execution from RTL to GDSII, ensuring architecture, implementation, and ...

Etched

Head of Performance Visibility

San Jose, CA · On-site

$195K/yr

Etched is an AI chip startup that designs and manufactures hardware systems optimized for artificial intelligence model inference workloads. Founded in 2022, the company is headquartered in San Jose ...

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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 is an AI chip?

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.

What cities are hiring for Ai Chip jobs? Cities with the most Ai Chip job openings:
What states have the most Ai Chip jobs? States with the most job openings for Ai Chip jobs include:
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 August 2026, with employment types broken down into 5% Internship, 85% Full Time, 5% Part Time, and 5% Contract. Highlights an 90% In-person, 5% Hybrid, and 5% Remote job distribution.

Solution Architect - US

FuriosaAI, Inc.

San Francisco, CA • On-site

$110 - $150/hr

Other

Posted 6 days ago

Job description

FuriosaAI is looking for a Solutions Architect to bring the full potential of our powerful RNGD chips/servers to our customers by acting as the primary technical authority in AI/LLM model deployments. From running POCs to benchmarking and debugging, you will translate RNGD’s powerful system to real-world deployments of customers’ models, empowering customers with FuriosaAI’s powerful solutions.

If you are interested in providing the technical expertise in challenging the current status-quo of AI infrastructure in real-world environments, join us in our path to a sustainable future of AI.

What You’ll Do
  • Own end-to-end technical enablement for US customers deploying AI models on FuriosaAI's RNGD NPU using the Furiosa SDK
  • Develop POCs, benchmarking studies, and live debugging sessions directly in customer environments
  • Act as the technical authority to the US BD/Sales team during pre-sales and enterprise evaluations; translate deep technical capability into business value for engineering and C-suite audiences
  • Develop deep, current expertise in FuriosaAI's hardware and software stack and demonstrate it at US technical forums, AI conferences, and customer workshops
  • Onboard and train customers on integration patterns, optimization workflows, and best practices post-purchase
  • Serve as a technical feedback loop from US customers back to Seoul HQ product and engineering teams
Qualifications
  • 2–5 years in a US customer-facing technical role: Solutions Architect, Sales Engineer, Forward Deployed Engineer, or equivalent at an AI infra, cloud, or semiconductor company
  • Actively current on the AI/LLM landscape — tracking model releases, inference frameworks, and serving stack evolution in real time
  • Hands‑on experience with modern inference stacks: vLLM, SGLang, TensorRT‑LLM, Triton Inference Server, or similar
  • Hands‑on experience with agent and orchestration frameworks: LangChain, LlamaIndex, LangGraph, AutoGen, or MCP‑based tooling
  • Proficiency in Python; comfortable with DNN frameworks (PyTorch, TensorFlow)
  • Strong written and verbal communication — able to engage credibly with ML engineers at frontier labs and VP/C‑suite executives
  • Authorized to work in the US; able to travel to customer sites and to Seoul HQ periodically
Preferred Qualifications
  • Prior experience at a US AI chip company, cloud silicon team, or AI infrastructure startup
  • Familiarity with NPU/GPU accelerator ecosystems, PCIe integration, and data center hardware deployment
  • Experience with inference optimization: quantization, kernel tuning, batching strategies, memory bandwidth optimization
  • Proficiency in C, C++, or Rust
  • Experience working with distributed or cross‑timezone engineering teams
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