Neurophos
Staff Systems Engineer, Calibration, Bring-Up & Verification
$185K–$215K
Austin, Texas · On-site · Staff · Full-time · Posted Sep 18, 2026
- Experience
- 5+ years of professional experience in calibration algorithm development, system bring-up, or verification of complex electro-optic or mixed-signal systems.
- Education
- MS or PhD in Electrical Engineering, Applied Physics, or a closely related field.
About the job
Own calibration architecture, integration, bring-up, verification, and laboratory characterization for an optical vector-matrix multiplication engine.
What you'll do
- Design calibration algorithms and signal-processing methods to correct optical phase, amplitude, and timing while meeting accuracy targets.
- Specify calibration hardware and software interfaces, and lead system integration, laboratory bring-up, diagnostics, verification, and characterization.
- Develop calibration and test software, correlate measured performance with models, and mentor engineers.
What they ask for
- MS or PhD in Electrical Engineering, Applied Physics, or a closely related field, emphasizing control systems, signal processing, or mixed-signal systems.
- Strong control and optimization theory, including feedback control and methods such as convex optimization, gradient descent, or search algorithms.
- Hands-on experience bringing up and debugging complex hardware with lab equipment, and proficiency in calibration/test software using Python and/or MATLAB.
- Understanding of analog and mixed-signal impairments and digital hardware design principles sufficient to specify implementable calibration hardware.
Nice to have
- Practical DSP experience, such as spectral analysis, correlation, or adaptive filtering, in calibration or measurement loops.
- Familiarity with Cadence Virtuoso and Spectre; exposure to Bayesian optimization, machine learning for calibration, or statistical design of experiments.
Pay
$185K – $215K (base salary)
Tools
Python, MATLAB, Cadence Virtuoso, Spectre
AI focus
Calibration and system verification for optical hardware designed to accelerate large-scale AI inference.
Model-written summary · the original posting is authoritative