Metasurface Simulation Engineer

Neurophos•Austin, TX

18d•Onsite

About The Position

At Neurophos, listed as one of EE Times’ 2025 100 Most Promising Start-ups, we are revolutionizing AI computation with the world’s first metamaterial-based optical computing platform. Our design addresses the traditional shortcoming of silicon photonics for inference and provides an unprecedented AI engine with substantially higher throughput and efficiency than any existing solution. We've created an optical metasurface with 10,000x the density of traditional silicon photonics modulators. This enables a solution with 100x gains in power efficiency for neural network computing without sacrificing throughput; we've made improvements there, too. By integrating metamaterials with conventional optoelectronics, our compute-in-memory optical system surpasses existing solutions by a wide margin and enables truly high-performance and cost-effective AI compute. Join us to shape the future of optical computing. Location: Austin, TX. Full-time onsite position. Position Overview We are seeking a Metasurface Simulation Engineer to play a vital role in advancing our state-of-the-art AI compute accelerators based on silicon photonics and free-space optics. This position focuses on developing simulation methodologies and conducting electromagnetic numerical simulations to design, optimize, and validate the performance of our revolutionary photonic architecture. You will work closely with a world-class team of theoreticians, physicists, optical engineers, and system engineers to model and iterate on system designs. If you are passionate about pushing the boundaries of photonic technology and thrive in a collaborative, innovative environment, this is your opportunity to make a transformative impact.

Requirements

PhD in Electrical Engineering, Physics, Optics, or a related field.
3+ years of hands-on experience performing electromagnetic numerical simulations for optical or photonic systems.
Proven expertise with commercial simulation software (e.g., HFSS, COMSOL, Lumerical).
Deep understanding of electromagnetic principles and their application to metasurfaces and photonic systems.
Experience with large-scale metasurface array modeling, including Floquet analysis, diffraction orders, and free-space optical propagation.
Deep understanding of vector calculus.
Experience with scripting (e.g., Python) for automation of simulation setups and data analysis.
Demonstrated ability to produce and present technical reports to diverse audiences, including technical peers and executive stakeholders.
Strong teamwork and communication skills, with a track record of thriving in collaborative, interdisciplinary environments.
Experience working independently to solve complex simulation challenges.

Nice To Haves

Background in metasurface design or nanophotonic modeling.
Familiarity with metasurfaces, spatial light modulators, or other advanced photonic components.
Experience with open-source or custom EM solvers.
Exposure to multi-physics simulations.
Knowledge of AI hardware architectures or neural network computing applications.
Hands-on experience designing custom electromagnetic simulation frameworks or high-fidelity metasurface models.

Responsibilities

Develop and refine simulation methodologies to model metasurfaces and photonic systems for AI compute acceleration.
Design, set up, and execute electromagnetic numerical simulations using commercial software and in-house solvers to demonstrate groundbreaking AI compute functionality.
Incorporate fabrication tolerances, process variations, and yield considerations into simulation models to ensure designs are manufacturable and robust in real-world fabrication processes.
Perform statistical analysis and generate detailed technical reports to document simulation results and system capabilities.
Present findings to both technical teams and executive leadership with clarity and precision.
Collaborate with interdisciplinary teams to integrate simulation insights into the broader system architecture and refine design iterations.
Troubleshoot complex simulation models and optimize workflows for accuracy and computational efficiency.