About Etched
Etched is building hardware for frontier intelligence. We co-design chips, racks, software, and manufacturing to deliver best-in-class throughput and latency across both prefill and decode workloads. Our first products are heavily focused on inference. 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 a Design Verification Engineer to join our Systems/Performance Verification team. You will ensure the custom IPs powering our chips — including systolic arrays, DMA engines, and NoCs — are robust, high-performance, and silicon-ready. This role demands creativity, deep technical ability, and the drive to tackle complex verification challenges. You will collaborate with architects, RTL designers, and SW/FW/emulation teams to validate correctness and performance across the full hardware-software stack.
Key responsibilities
Work closely with architects and RTL designers on verifying the performance features of the design and correlating with performance models (both pre-silicon and post-silicon).
Work closely with software and application developers on identifying performance bottlenecks and tuning the software.
Develop test plans and test infrastructure/tools for performance tuning, correlation, and verification.
Improve and maintain the architectural performance models.
Develop tests in SystemVerilog, Python, or vectors to debug and correlate the RTL and performance model.
Develop SystemVerilog or Python-based checkers for verifying the performance features.
Develop coverage monitors and analyze coverage to ensure all performance features are covered.
Debug performance issues and conduct performance tuning on silicon.
Drive end-to-end performance tuning, ensuring optimal hardware utilization, software efficiency, and architectural alignment across the ASIC design lifecycle.
You may be a good fit if you have
Strong understanding of digital design, RTL, and ASIC design flows.
Hands-on experience with performance verification, simulation, and modeling.
Comfortable developing checkers, coverage monitors, and testbenches in SystemVerilog.
Skilled in writing Python scripts for automation, data analysis, and performance modeling.
Experience building and maintaining performance models for chip subsystems.
Understanding of memory hierarchies, pipelines, interconnects, and compute accelerators.
Familiarity with performance bottleneck analysis, compiler optimizations, and workload tuning
Some exposure to kernel level performance metrics and profiling tools.
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
Unlimited compute budget subject to ROI justification
How we’re different
Etched believes in the Bitter Lesson. We are the first inference-focused frontier AI system, betting early on transformer and transformer-like architectures and on increasing model sizes. Our addressable market is the entirety of inference, unlike many of our competitors.
We are a fully in-person team in San Jose (Santana Row), 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 and work across disciplines as needed.
What you need to know about the Austin Tech Scene
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
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- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center
