Neurophos develops photonic AI inference chips that aim to deliver exaflop-scale performance with drastically lower power consumption than traditional GPUs.
ABOUT NEUROPHOS The demand for new data centers and AI compute is rapidly outpacing the planet's energy capacity. Digital solutions are hitting a power wall as we approach the physical limits of traditional silicon. Conquering this bottleneck means rethinking the fundamental architecture of inference compute. The industry's current path can't meet the need, so we're taking a different approach. Instead of traditional electronic circuits, we use silicon photonics and an active, programmable metasurface to perform matrix multiplications at the speed of light. Our optical cells are 10,000x smaller than traditional photonic components, enabling unprecedented density. By using photonics instead of electricity, our chips become more efficient as they scale. This architecture will deliver up to 100 times the energy efficiency of existing solutions while significantly improving performance for large-scale AI inference. We’ve assembled a world-class team of industry veterans and recently raised a $110M Series A https://www.neurophos.com/110m-raise led by Gates Frontier. Participants include M12 (Microsoft’s Venture Fund), Carbon Direct Capital, Aramco Ventures, Bosch Ventures, Tectonic Ventures, Space Capital, and others. Join us and shape the future of computing! POSITION OVERVIEW We are seeking a talented Firmware Engineer to join our engineering team. This role is focused on low-level firmware development for our novel LLM accelerator architecture. You will develop code for the firmware layer that directly controls our custom hybrid optical-electronic compute hardware, ensuring reliable operation and optimal performance. LOCATION Austin, TX KEY RESPONSIBILITIES Firmware Development: - Contributing to low-level firmware to orchestrate execution of LLM workloads across hardware accelerator components - Contributing to system and board management of such a system - Create debugging and profiling tools for firmware and hardware interaction System Integration: - Collaborate with hardware engineers to define software-hardware interfaces - Optimize end-to-end performance from application layer to hardware execution - Develop comprehensive testing and validation frameworks - Create documentation and specifications for firmware interfaces - Support customer integration and provide technical guidance QUALIFICATIONS - Education: Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or related field - Experience: 3–5 years of professional experience in firmware engineering, embedded systems, or low-level systems programming - Programming: High proficiency in embedded C++ (essential), Python for tooling and automation - Embedded Systems: Experience with embedded systems programming and hardware interfaces - Systems Knowledge: Familiarity with computer architecture, memory hierarchies, and parallel computing concepts - Hardware Interfaces: Experience with hardware communication protocols and register-level programming PREFERRED SKILLS - Education: Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or related field - Bus Protocols: Experience with lower speed peripheral busses (I2C/SPI/UART/CAN/LIN), Some experience with PCIe interfaces. Some experience with Ethernet interfaces. - Embedded Processors: Experience with embedded processor architectures (ARM, RISC-V, or similar) and associated toolchains (strongly preferred) - Virtual Platforms: Experience with early firmware development on virtual platforms and/or fast C simulators (preferred) - Cross-Compilation: Hands-on experience with cross-compiler toolchains (preferred) - Containerization: Experience with Docker containers for development and delivery (preferred) - Parallel Debugging: Experience debugging parallel and asynchronous programs (strongly preferred) - Real-Time Systems: Experience with bare metal programming and RTOS (FreeRTOS, Zephyr, or similar) (preferred) - AI-Assisted Development: Experience with structured, human-supervised AI/agentic coding workflows (preferred) - Multi-Node Systems: Experience with multi-node embedded systems, including inter-node communication and coordination (strongly preferred) - Multi-Processor Systems: Experience with multi-processor systems, including IPC and shared memory coordination (preferred) - Adaptive Firmware: Experience designing adaptive and retargetable firmware architectures (preferred) - OTA Updates: Experience with over-the-air update systems for embedded devices (preferred) - RTL Familiarity: Ability to read and understand RTL code for debugging and hardware-software co-design - ML Hardware: Experience with AI/ML accelerators (GPUs, TPUs, FPGAs) and their programming models - Performance Optimization: Experience with high-performance computing and low-latency system design - Thermal/Power Management: Experience with thermal management and power optimization in embedded systems - LLM Knowledge: Familiarity with Large Language Model architectures and their computational requirements (preferred) - High Speed Protocols: Some familiarity or understand of AMBA, AXI, PCIe, on processors and ROCv1/2, Infiniband over networks TECHNICAL SKILLS - Programming Languages: Embedded C++ (essential), Python, Assembly - Bus Protocols: I2C, SPI, UART, or low-speed serial protocols. Ethernet familiarity. - Embedded Processors: ARM Cortex-M/A, RISC-V, or similar; associated toolchains and debugging - Embedded Platforms: Bare metal programming, FreeRTOS, Zephyr, or similar RTOS - RTL & Verification: Verilog/SystemVerilog (reading comprehension), ModelSim, Questasim, or similar simulation tools (nice to have) - Hardware Interfaces: Register-level programming, memory-mapped I/O. - Driver Methodologies: Polling, Interrupt and DMA based hardware interactions - Distributed Embedded: Inter-node communication, message passing, distribut