Etched.ai is an AI infrastructure company building rack-scale and frontier inference systems.
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. Key responsibilities - Develop comprehensive performance models and projections for our architecture across varying workloads and configurations - Profile and analyze deep learning workloads on our hardware to identify micro-architectural bottlenecks and influence optimization opportunities - Drive hardware/software co-optimization by identifying where architectural features can unlock performance improvements - Run regressions and validate performance models against real systems and silicon - Inform next-generation architectural decisions by pathfinding across system and silicon options during design, proof-of-concept, and architecting phases You may be a good fit if you have at least one of the following: - Strong performance modeling and analysis skills with experience building analytical-based or simulation-based performance models - Solid understanding of computer architecture and micro-architecture, particularly for accelerators - Experience profiling and analyzing deep learning workloads on hardware accelerators (GPUs, TPUs, ASICs, FPGAs, or others) - Solid software engineering fundamentals with an eye toward auditability and maintainability Strong candidates may also have - Deep knowledge of GPU architectures and/or programming models like CUDA - Experience mapping models to multi-chip inference systems - Familiarity with transformer model architectures and inference serving optimizations - Experience with architecture simulators and performance modeling tools (gem5, trace-driven simulators, custom models) - Exposure to ASIC, FPGA, or CGRA-based accelerator development and hardware/software co-design principles - Published research in computer architecture, ML systems, or hardware acceleration Benefits - Medical, dental, and vision packages with generous premium coverage - $500 per month credit for waiving medical benefits - Housing subsidy of $2k per month for those living within walking distance of the office - Relocation support for those moving to San Jose (Santana Row) - 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 http://www.incompleteideas.net/IncIdeas/BitterLesson.html. 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.