Teams at Lightmatter

Lead machine learning infrastructure research for photonics-enabled AI systems. Build performance models for training and inference workloads, design rack-scale reference platforms, publish research and technical content, advise cross-functional teams, and lead a small team of machine learning engineers. The role requires deep expertise in AI systems, compute and networking technologies, performance evaluation, large language models, and academic research.

Develop and maintain photonics Process Design Kits, including Python-based layout libraries, compact behavioral models, test structures, and automated verification pipelines. Validate models against silicon measurements through data fitting and statistical analysis. Collaborate with multidisciplinary engineering teams to support large-scale photonic integrated circuit tape-outs. The role requires advanced photonic device physics, circuit simulation, Python programming, layout automation, and experience with foundry PDKs and design verification.

Design and own firmware test automation frameworks, hardware-in-the-loop infrastructure, CI/CD integration, diagnostics, telemetry, and test reporting for photonic hardware. Debug failures across firmware, boards, instruments, fixtures, and test code. Define test strategies, improve framework reliability, support embedded systems interfaces, participate in design reviews, document architecture, and mentor engineers.