By burning the transformer architecture into our chips, we’re creating the world’s most powerful servers for transformer inference.
By burning the transformer architecture into our chips, we’re creating the world’s most powerful servers for transformer inference.
What they do: Designs AI chips (Sohu) optimized for transformer-model inference
Stage / funding: Series A (announced Jun 25, 2024), reported ~$120M round; total funding reported $625.4M
Founded: Around 2022
Team size: Approximately 317 employees
AI inference performance and efficiency for transformer models
2022
Computer Hardware Manufacturing
$120,000,000
Round reported to include multiple institutional and angel participants
“Includes institutional VCs and prominent angel/backer participation (e.g., Two Sigma Ventures, Peter Thiel, Thomas Dohmke)”
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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 We are seeking highly motivated and skilled Pod Networking Software Engineers to join our System Software team. This team plays a critical role in developing, qualifying, and optimizing high-performance networking solutions for large-scale inference workloads. As a Pod Software Engineer, you will focus on developing and qualifying software that drives communication amongst Sohu inference nodes in multi-rack inference clusters. You will collaborate closely with kernel, platform, and telemetry teams to push the boundaries of peer-to-peer RDMA efficiency.
Key Responsibilities
Representative Projects
Must-Have Skills And Experience
Nice-to-Have Skills And Experience
Ideal Background
Benefits
Compensation Range
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 West San Jose, 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.