Staff Systems Engineer
Neurophos
Staff Systems Engineer
Neurophos
Optical metasurface AI accelerators
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 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!
Location: Austin, TX. Full-time onsite position.
Reports To: Chief Systems Engineer
FLSA Status: Exempt
We are seeking a highly skilled Systems Engineer to own calibration architecture, system integration, and verification for our optical vector-matrix multiplication (OVMM) engine. This role is central to closing the gap between a system that is designed to meet its accuracy targets and one that demonstrably does so on the bench: you will devise the calibration algorithms that correct optical phase, amplitude, and timing across many channels, specify the analog and digital hardware structures needed for real-time calibration execution, define the bring-up and verification strategy, and personally drive laboratory characterization of the hardware.
You will spend much of your time devising calibration algorithms grounded in control theory and signal processing, and the rest of it hands-on in the lab, bringing up hardware, running verification plans, characterizing performance, and tracking down exactly where measured behavior departs from the model. If you combine control-theory and signal-processing depth with genuine enthusiasm for lab work, this role will let you own the path from calibrated silicon to a working, verified system.
Primary Responsibilities
Calibration Architecture: Define the calibration architecture for the OVMM system, and scope and size the algorithms needed to correct optical phase, amplitude, and timing across many transmit and receive channels.
Calibration Algorithm Development: Design, implement, and optimize calibration algorithms, applying control theory and optimization techniques to minimize calibration time while meeting system accuracy targets.
Signal Processing for Calibration: Design and implement signal processing techniques used within calibration loops to enhance measurement SNR through coding gain and noise bandwidth reduction.
Calibration Data Compression: Develop techniques and algorithms to compress calibration data and minimize on-chip and off-chip storage requirements.
HW/SW/Control Interaction: Specify the calibration controller behavior, apply paths, and digital hardware structures needed to execute calibration in silicon, and define the calibration software and firmware interfaces that drive them.
System Integration Strategy & Bring-Up: Define the system integration strategy, plan the integration sequence, and lead laboratory bring-up and debug of the assembled system, establishing acceptance criteria at each subassembly boundary.
Observability & Diagnostics: Define system-level test, diagnostic, and observability requirements so that bring-up, calibration, and field operation can all distinguish a healthy system from a degraded one.
Verification & Characterization: Develop verification plans, execute performance characterization in the lab, and correlate measured results with modeled predictions, identifying and root-causing gaps between the two.
Secondary Responsibilities
Develop calibration control and test software (primarily Python) used both in the lab during bring-up and as the basis for production calibration flows.
Supply the Signal-Path Performance & Modeling team with calibration accuracy budgets and sensitivity data derived from lab measurements.
Flag to the Architecture & Requirements team any interface or requirement that impedes calibration, bring-up, or verification.
Mentor engineers in calibration algorithm design, bring-up practice, and laboratory characterization methodology.
Degree: MS or PhD in Electrical Engineering, Applied Physics, or a closely related field, with emphasis on control systems, signal processing, or mixed-signal systems.
Experience: 5+ years of professional experience in calibration algorithm development, system bring-up, or verification of complex electro-optic or mixed-signal systems.
Control & Optimization Theory: Strong foundation in feedback control (stability analysis, sampled-data systems) and optimization methods (convex optimization, gradient descent, search algorithms), with demonstrated ability to formulate a calibration problem as a formal optimization problem and solve it efficiently.
Analog System Understanding: Deep understanding of analog and mixed-signal impairments including noise (thermal, shot, flicker), component mismatches, nonlinearities (compression, harmonic distortion), bandwidth limitations, and their impact on system-level performance metrics (SNR, BER, ENOB). Ability to theoretically predict calibration performance from first principles.
Digital Hardware Awareness: Good understanding of digital hardware design principles, including logic synthesis, area and power estimation, state machine design, and fixed-point arithmetic, sufficient to specify calibration hardware that is implementable within realistic silicon constraints. Familiarity with RTL design concepts and hardware-software partitioning.
Lab & Verification: Hands-on experience bringing up and debugging complex hardware using oscilloscopes, spectrum/network analyzers, and optical test equipment, and correlating measured performance against a model.
Software for Calibration: Proficiency developing calibration and test software (Python and/or MATLAB), including control loops, data acquisition, and automated characterization scripts, sufficient to run and iterate on lab measurements independently.
Communication: Excellent communication skills for cross-functional collaboration with analog IC designers, digital designers, photonic device engineers, and system architects.
Practical experience with digital signal processing techniques, including spectral analysis, correlation, and adaptive filtering, applied within calibration or measurement loops.
Familiarity with Cadence Virtuoso and Spectre for validating calibration-relevant behavioral models against circuit-level simulation.
Exposure to Bayesian optimization, machine learning for system calibration, or statistical design of experiments.
Experience with optical transceiver calibration, phased-array beamforming, or ADC/DAC calibration.
This is an opportunity to play a pivotal role in an innovative startup redefining the future of AI hardware. Work on game-changing technology at the intersection of photonics and AI as part of a collaborative, brilliant team. You’ll contribute to a platform that redefines computational performance and accelerates the future of artificial intelligence. Come help us bring this transformative technology to the world.
Join a team that invests in your future and your well-being. At Neurophos, we offer:
100% coverage of base health plan premiums for you and your dependents, plus HSA contributions.
Unlimited PTO. No rigid vacation banks, just a focus on delivery.
401(k) matching and stock option opportunities to ensure our success is your success.
Full suite of voluntary benefits, including Dental, Vision, Life, Hospital, Critical Illness, and Accident insurance.
Personalized Benefits. Choose the plans that fit your life and take the cash back for those that don’t.
Neurophos designs AI accelerator chips built with optical metasurfaces and silicon photonics to deliver high-density, energy-efficient AI computation for data centers. Its processors are designed to shrink optical components by about 8000x, increasing compute power per dollar spent and reducing both capital and operating expenditures. The product works by using optical processing techniques that handle AI inference workloads more efficiently than traditional GPUs or electronic AI accelerators, enabling faster throughput with lower power use. Neurophos differentiates itself by combining optical metasurfaces with silicon photonics to achieve higher density and energy efficiency, targeting data centers and enterprises that need scalable, cost-sensitive AI inference. The company aims to reshape the AI landscape by offering faster, denser, and more energy-efficient AI computation while lowering the total cost of ownership for data centers.
Explore more opportunities at Neurophos