Edge Compute Architect for Optical Systems

Key Responsibilities

• Define dataflow and compute architectures for ASIC- or FPGA-based near-sensor processing, including streaming pipelines, memory and bandwidth budgets, latency targets, and power constraints
• Map computational imaging, computer vision, and ML inference algorithms to hardware-feasible forms; specify numerical precision and quantization strategies
• Own real-time performance budgeting, including throughput and latency modeling, and drive architecture decisions that enable real-time reconstruction and analysis
• Partition functionality across ASIC/FPGA, embedded processors, and software; define interfaces and performance requirements
• Co-design end-to-end sensing systems—optics, sensor, readout, and compute—and perform trade studies across SNR, resolution, dynamic range, throughput, latency, robustness, and complexity
• Develop or adapt physics-based models of sensor system performance and validate predictions against laboratory and field measurements
• Lead system-level prototyping and integration including sensor, optics, electronics, and FPGA, as well as instrumentation and data pipelines
• Partner with digital and mixed-signal design teams to iterate on designs and evaluate results
• Produce architecture documentation, performance budgets, and technical reports; communicate clearly with internal and external stakeholders
• Contribute to IP generation and platform planning for advanced sensor systems

Qualifications

• PhD with relevant research or industry experience, or MS with relevant and extensive industry experience, in EE/CS/Optical Engineering/Applied Physics or related
• Deep background in signal and image processing, including experience applying modern machine-learning and AI approaches in resource-constrained sensing systems
• Strong publication record in peer-reviewed journals and conferences

Soft Skills

• Eager to work on challenging, open-ended problems and understand their broader application context
• Excellent problem-solving skills with a creative, persistent approach to complex technical challenges
• Strong communication skills, with the ability to present complex information clearly and concisely to diverse audiences
• Able to work independently and collaboratively in a fast-paced, interdisciplinary research environment