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
Position OverviewWe 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, 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.
Key ResponsibilitiesPrimary Responsibilities
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.
Design, implement, and optimize calibration algorithms, applying control theory and optimization techniques to minimize calibration time while meeting system accuracy targets.
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.
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.
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.
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 in Python) used both in the lab during bring-up and as the basis for production calibration flows.
Supply the Signal-Path Performance & Modeling focus area with calibration accuracy budgets and sensitivity data derived from lab measurements.
Flag to the Architecture & Requirements focus area any interface or requirement that impedes calibration, bring-up, or verification.
Mentor engineers in calibration algorithm design, bring-up practice, and laboratory characterization methodology.
MS or PhD in Electrical Engineering, Applied Physics, or a closely related field, with emphasis on control systems, signal processing, or mixed-signal systems.
5+ years in calibration algorithm development, system bring-up, or verification of complex electro-optic or mixed-signal systems.
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.
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.
Proficiency developing calibration and test software (Python and/or MATLAB)—control loops, data acquisition, and automated characterization scripts—sufficient to run and iterate on lab measurements independently.
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—spectral analysis, correlation, and adaptive filtering—applied within calibration or measurement loops.
Experience specifying digital hardware for calibration (register maps, state machines, fixed-point arithmetic) sufficient to collaborate effectively with digital design engineers.
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.
Skills Required
- MS or PhD in Electrical Engineering, Applied Physics, or a closely related field, emphasizing control systems, signal processing, or mixed-signal systems.
- 5+ years of experience in calibration algorithm development, system bring-up, or verification of complex electro-optic or mixed-signal systems.
- Strong foundation in feedback control, including stability analysis and sampled-data systems.
- Experience with optimization methods, including convex optimization, gradient descent, or search algorithms.
- Ability to formulate calibration problems as formal optimization problems and solve them efficiently.
- Hands-on experience bringing up and debugging complex hardware using oscilloscopes, spectrum/network analyzers, and optical test equipment.
- Experience correlating measured hardware performance against system models.
- Proficiency developing calibration and test software in Python and/or MATLAB.
- Experience with control loops, data acquisition, and automated characterization scripts.
- Excellent communication skills for cross-functional collaboration with analog IC, digital, photonic device, and systems engineering teams.
- Practical experience with digital signal processing, including spectral analysis, correlation, and adaptive filtering.
- Experience specifying digital hardware for calibration, including register maps, state machines, and fixed-point arithmetic.
- Familiarity with Cadence Virtuoso and Spectre.
- Experience with Bayesian optimization, machine learning for system calibration, or statistical design of experiments.
- Experience with optical transceiver calibration, phased-array beamforming, or ADC/DAC calibration.
Neurophos Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Neurophos and has not been reviewed or approved by Neurophos.
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Healthcare Strength — Job postings indicate the company covers 100% of base health plan premiums for employees and dependents and contributes to HSAs. Listings also reference dental, vision, and other voluntary coverages.
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Leave & Time Off Breadth — Unlimited PTO is advertised with an emphasis on delivery rather than accruals. Notes in postings suggest clarifying typical usage and any minimums.
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Retirement Support — A 401(k) with employer matching is listed alongside stock option opportunities. This pairing signals structured retirement support in addition to equity participation.
Neurophos Insights
What We Do
Neurophos is an Austin-based semiconductor company developing high-performance, energy-efficient photonic AI inference chips. 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 for an optical system. As AI adoption accelerates, data centers face significant power and scalability challenges. Traditional solutions are struggling to keep up, leading to rapidly rising energy consumption and costs. We’re solving both problems with an OPU that integrates over one million micron-scale optical processing components on a single chip. This architecture will deliver up to 100 times the energy efficiency of existing solutions while significantly improving large-scale AI inference performance. 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. We have also been recognized on the EE Times Silicon 100 list for several consecutive years. Join us and shape the future of optical computing!
Why Work With Us
This is an opportunity to work on a game-changing technology at the intersection of photonics and AI. You’ll contribute to a platform that redefines computational performance and accelerates the future of artificial intelligence.







