Hardware Test Infrastructure Engineer

Efficient is developing the world’s most energy-efficient general-purpose computer processor. Efficient’s patented technology uses 100x less energy than state of the art commercially available ultra-low-power processors and is programmable using standard high-level programming languages and AI/ML frameworks. This level of efficiency makes perpetual, pervasive intelligence possible: run AI/ML continuously on a AA battery for 5-10 years.

Our platform’s unprecedented level of efficiency enables IoT devices to intelligently capture and curate first-party data to drive the next major computing revolution We are seeking a strong hardware infrastructure engineer to develop and scale ATLAS: Efficient’s critical hardware regression testing and performance profiling infrastructure. ATLAS supports automated benchmarking and validation of both our company's products and competitor hardware, providing essential data that drives engineering and product decisions. This role requires a unique set of skills that span both embedded software development as well as typical cloud compute platforms.

The ideal candidate must be a full-stack infrastructure engineer who is equally comfortable writing Go services, managing Kubernetes environments, debugging low-level test programs, and working with a wide variety of embedded hardware such as FPGA, Ambiq, Apollo, PIC32 and Efficient E1.

Key Responsibilities

Regression Testing Performance Profiling Infrastructure Embedded Hardware Deployment, Maintenance Troubleshooting: Install new embedded hardware platforms, manage deployed hardware, and perform debug and failure analysis of hardware issues. Test Program Development: Write, port, and maintain low-level c/c++ test programs that run on a diverse set of hardware targets to measure performance, power, and functional behavior. Reliability Observability: Monitor system health, triage failures, perform root-cause analysis, and continually improve the resilience, robustness, and performance of the infrastructure.

Tooling Automation: Build Python tooling and scripts to automate workflows, parse results, generate reports and drive developer facing performance dashboards. Kubernetes Infrastructure: Maintain and evolve Kubernetes deployments, including job queueing, load balancing, scheduling, and resource management for hardware-attached worker nodes Server, Client Database Development: Design, implement, and maintain Go-based server and client applications. Manage PostgreSQL (operations data store) and Redis (caching layer), including schema design, query optimization, migrations, and reliability improvements.

Required Qualifications

Experience Hands-on embedded hardware and software development experience, including working with embedded toolchains and bring-up of new hardware platforms. Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field — or equivalent practical experience. Lead level experience with 5+ years in a cloud and embedded hw infrastructure, test engineering, and full-stack systems role.

Excellent written, verbal, and technical communication skills, with the ability to clearly document complex systems, and lead discussions across teams. A collaborative spirit, with the ability to support and influence multiple engineering teams, balancing competing priorities. Go: Strong proficiency, including experience building production services with HTTP APIs and WebSockets C/C++: Demonstrated ability to write, debug, and maintain systems-level or test code.

Python: Solid experience using Python for tooling, automation, and scripting Kubernetes: Hands-on experience operating and maintaining Kubernetes environments, including queueing and load balancing patterns.

Qualifications

Experience Experience with JTAG/SWD debugging tools and workflows Familiarity with energy and power measurement tools (e.g., po