Firmware Engineer (Taiwan)

About Etched

Etched is building the world’s first AI inference system purpose-built for transformers - delivering over 10x higher performance and dramatically lower cost and latency than a B200. With Etched ASICs, you can build products that would be impossible with GPUs, like real-time video generation models and extremely deep & parallel chain-of-thought reasoning agents. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history.

Job Summary

• Co-Develop cutting-edge software optimized across hardware and software driving the full potential of very large transformer models.

• Solve challenging problems across the full stack, from low-level drivers and APIs to high-level applications and frameworks.

• Contribute to the development of AI solutions that will revolutionize industries like natural language processing, chain of reasoning automation, generative media.

You may be a good fit if you have

• Bachelor's degree or equivalent practical experience.

• 3 years of experience in software development, and with data structures/algorithms.

• 3 years of experience developing and testing software on launching products.

• 3 years of experience with firmware design, implementation, and troubleshooting.

• 3 years of experience with embedded architectures, IO technologies (I2C, SPI, PCIe, DRAM etc.), as well as concepts like scalability, fault tolerance, and consistency.

Strong candidates may also have experience with (Nice-to-have qualifications)

• Master’s degree Computer Science, or a related technical field.

• Experience resolving customer-related issues.

• Experience solving ambiguous problems.

• Excellent verbal and written communication skills.

Benefits

• Competitive compensation packages including generous equity packages

• Comprehensive insurance coverage and other top-of-market benefits

How we’re different

Etched believes in the Bitter Lesson. We think most of the progress in the AI field has come from using more FLOPs to train and run models, and the best way to get more FLOPs is to build model-specific hardware. Larger and larger training runs encourage companies to consolidate around fewer model architectures, which creates a market for single-model ASICs.

We are a fully in-person team in San Jose and Taipei, and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both as needed.