RTL Design Engineer

Job Title

RTL Design Engineer

Role Summary

As an RTL Engineer on Etched's ASIC team in San Jose, you will develop and verify RTL blocks for AI inference chips and ensure correct, efficient operation of designs. You will collaborate with microarchitecture, synthesis, and verification teams to implement and validate functionality for high-performance transformer-oriented hardware.

Experience Level

Senior — typically 5+ years of RTL development experience.

Responsibilities

Primary responsibilities include design and verification of RTL blocks and collaborating across engineering teams.

• Develop, implement, and execute design verification strategies and testbenches for ASIC RTL.
• Design and optimize RTL blocks (e.g., floating-point math operators) for timing, area, and performance.
• Work with microarchitecture and synthesis teams to meet timing and area constraints.
• Debug functional and timing issues in simulation and synthesis flows; iterate on designs.
• Learn and apply architectural requirements for transformer-focused ML accelerators.

Requirements

Must-have technical skills and experience.

• At least 5 years of professional RTL development experience.
• Strong background in high-speed digital logic design.
• Proficiency with standard RTL design and synthesis tools.
• Experience with verification methodologies and writing testbenches.
• Ability to learn quickly about transformer architectures and related ML requirements.
• Available to start quickly and work in-person in San Jose, CA.

Nice-to-have:

• Experience with PCIe, Ethernet, or HBM technologies.
• Familiarity with transformer models and machine learning workflows.
• Understanding of numerical representations and functions (FP formats).
• Scripting experience (Python or similar) for automation and verification.

Education Requirements

Not specified.

About the Company

Company: Etched

Headquarters: San Jose, CA, United States

Etched develops purpose-built AI inference ASICs and systems optimized for transformer models, aiming to deliver significantly higher performance, lower cost, and lower latency than GPUs. The company focuses on enabling applications like real-time video generation and advanced reasoning agents, and is backed by leading investors and engineers.