This internship involves researching and developing GPU-accelerated techniques for deep learning, machine learning, and AI workloads. You will collaborate with technical experts to optimize complex algorithms, publish findings, and influence the design of next-generation hardware and software.
This role involves researching and developing GPU-acceleration techniques for high-performance computing applications in scientific computing, computational engineering, and data science. You will work closely with application developers and NVIDIA teams to optimize performance and influence next-generation GPU architectures.
This role involves laying out complex, high-layer-count PCBs for an innovative optical computing system. Responsibilities include controlled-impedance routing, BGA breakout, and managing the entire manufacturing process from schematic to fabrication release.
This role involves designing and maintaining a Python-based framework to model hardware and software latency, concurrency, and event-driven relationships for Lumai's photonic AI hardware. You will work closely with architecture and compiler teams to ensure the models are accurate and useful for decision-making, and may lead a small team.
This role involves planning, commissioning, and executing functional, electrical, mechanical, and environmental tests on imaging detectors and sub-systems for space and science applications. The engineer will develop test procedures, automate test equipment using scripting, and ensure compliance with ECSS standards. Work spans clean-room environments and office settings, supporting end-to-end verification across the project lifecycle.
This role involves programming, setting, and operating modern CNC milling machinery to produce large and complex components for high-integrity industries like nuclear, medical, and semiconductor. The position requires strong Heidenhain and 5-axis machining experience, with responsibilities including tooling selection, inspection, and quality documentation.
In this role, you will research and develop GPU-acceleration techniques for high-performance computing applications in scientific computing, computational engineering, and data science. You will work closely with application developers and NVIDIA teams to optimize performance and influence the design of next-generation GPU architectures and software platforms.
This role involves owning signal and power integrity across high-speed PCB designs, from pre-layout channel studies to post-layout analysis, material evaluation, and simulation correlation. The engineer will work closely with the ASIC team to ensure end-to-end channel and power integrity, and develop reusable design guidelines and model libraries.
