Machine Learning Co-Design Researcher

Join to apply for the Machine Learning Co-Design Researcher role at Etched

About Etched : Etched is building AI chips that are hard-coded for individual model architectures. Our first product (Sohu) only supports transformers, but has an order of magnitude more throughput and lower 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.

Key Responsibilities :

• Translate core mathematical operations from transformer models into optimized operation sequences for Sohu
• Develop and leverage a deep understanding of Sohu to co-design both HW instructions and model architecture operations to maximize model performance
• Implement high-performance software components for the Model Toolkit
• Collaborate with hardware engineers to maximize chip utilization and minimize latency
• Implement efficient batching strategies and execution plans for inference workloads
• Design and implement cutting edge inference time compute scaling methods
• Alter and fine-tune model architectures or inference time compute algorithms
• Contribute to the evolution of our system architecture and programming model

Representative projects :

You may be a good fit if you have :

Strong Candidates May Also Have Experience With :

Benefits :

Compensation Range : $150,000 - $275,000

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.

#J-18808-Ljbffr