
Infrastructure Engineer, Factory Acceleration at Etched (San Jose, CA)
Etched· San Jose, CA·
Role details
Etched at a glance
Transformer-specific ASICs and rack-scale systems that hardwire the transformer into silicon for faster, cheaper AI inference.
Etched designs transformer-specific ASICs and full rack-scale inference systems. Its Sohu chip hardwires the transformer architecture directly into silicon, trading a GPU's general-purpose flexibility for far higher throughput, lower latency, and better power efficiency on AI inference. Customers buy complete co-designed clusters, chip plus rack plus software, not standalone chips.
$800M raised · latest: $500M · led by Stripes · Dec 2025 (reported Jan 2026) · backed by Stripes, Peter Thiel, Ribbit Capital, VentureTech Alliance
Job description
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 Etched is seeking a Test Infrastructure Engineer to build and run the infrastructure behind factory testing of our AI systems, from new product introduction through mass production. You will join a new, small central team that owns making factory testing reliable, repeatable, and scalable. A factory test floor looks a lot like a small datacenter: hundreds of boards, servers, and racks under test at once, all running our test software and reporting results back. You will own that layer: the systems that provision and run test stations, move test results and logs into one reliable source of truth, and roll out new test software safely across factories. You will work closely with hardware, firmware, software, and production teams, and with our contract manufacturing partners.
Key Responsibilities
- Build and operate the test execution platform that runs factory tests across stations, servers, and racks, and keep it running reliably during factory hours.
- Provision and manage the Linux fleet on the factory floor: OS imaging and network boot, configuration management, and lifecycle automation for test stations and systems under test.
- Design and maintain the networking that test stations and racks depend on, working with factory partners on site.
- Build data pipelines that reliably capture every test run, its logs, and hardware genealogy into a central view of test history, yield, throughput, and unit history.
- Own versioned release, canary, and rollback of factory test packages so new test software reaches production safely and traceably.
- Build monitoring and alerting across factory infrastructure, and lead debugging when infrastructure issues block production.
- Integrate with contract manufacturers' factory systems (MES/SFIS) and with shared internal data platforms.
- Automate repetitive debug work, such as gathering evidence and grouping repeated failure signatures, and help build toward AI-assisted failure triage.
You may be a good fit if you have (Must-have qualifications)
- 3+ years of experience building and operating production infrastructure.
- Strong Linux administration skills: boot process, package management, systemd, storage, and debugging from the command line.
- Solid networking fundamentals: TCP/IP, DNS, DHCP, VLANs, VPNs, and how networks are laid out in server rooms or datacenters.
- Experience with distributed systems: services that run across many machines and keep working when some of them fail.
- Strong coding skills in Python, C++, or Rust. You build real tools and services, not only configuration.
- Experience with automation and configuration management (e.g. Ansible, Terraform) and CI/CD.
- Experience with monitoring and observability tools (e.g. Prometheus, Grafana) and debugging production issues.
- Bachelor's degree in Computer Science, Computer Engineering, or equivalent practical experience.
- Willingness to work onsite in San Jose or Taiwan and travel to manufacturing partners as needed.
Strong candidates may also have experience with (Nice-to-have qualifications)
- Bare-metal server fleets, lab or datacenter automation, or HPC clusters (e.g. PXE, Slurm).
- Server management interfaces such as BMC, IPMI, or Redfish.
- Manufacturing test infrastructure, test automation platforms, or factory software (MES, SFIS).
- Data pipelines for test results, yield analysis, or hardware genealogy.
- AI servers, GPU or accelerator systems, or other high-performance compute platforms.
- Working with contract manufacturers; Mandarin is a plus for Taiwan-based candidates.
- Bringing first-generation hardware into production at a fast-paced startup.
Benefits
- Competitive compensation packages including generous equity packages
- Comprehensive insurance coverage and other top-of-market benefits
How we’re different
Etched believes in the Bitter Lesson. We are the first inference-focused frontier AI system. Our addressable market is the entirety of inference, unlike many of our competitors. We are a fully in-person team in San Jose and Taipei, 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.
Why work at Etched
- Mission-driven, high-impact engineering: “Building the hardware for superintelligence” – the company is solving one of the hardest problems in compute (inference efficiency) with a focused team.
- Top-tier team and learning environment: Colleagues from Google, NVIDIA, Apple, Tesla, Broadcom, and Intel; exposure to full-stack chip-to-system design.
- In-office culture: All roles are in-office (Cupertino and San Jose, CA). The company emphasizes on-site collaboration for hardware development. Notable perks are not heavily advertised, but compensation is competitive for the AI hardware space (equity-heavy).
- Growth trajectory: 141% headcount growth YoY, hundreds of open roles, and a $5B valuation signal strong backing and career acceleration potential.
- Intellectual challenge: Work on chip simulation, RTL design, system validation, or software infrastructure for cutting-edge AI inference.