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.

• Experience in software development, and with data structures/algorithms.

• Experience developing and testing software on launching products.

• Experience with firmware design, implementation, and troubleshooting.

• 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

• Medical, dental, and vision packages with generous premium coverage

  • $500 per month credit for waiving medical benefits

• Various wellness benefits covering fitness, mental health, and more

• Daily lunch + dinner in our office

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 have a growing presence in Austin and a core team in San Jose (Santana Row), and we greatly value engineering skills. We do not have strict boundaries between engineering and research, and we expect all of our technical staff to contribute to both as needed.

This role is based in our Austin office, with regular time spent working alongside the team in San Jose. During the first quarter, expect to spend approximately two weeks per month at our San Jose headquarters to ramp quickly. After that, this shifts to roughly one week per month for ongoing collaboration.