Embedded Engineer at Gridware translating DSP algorithms into production-ready implementations. Collaborating with ML scientists and firmware teams for embedded platforms with strict resource constraints.
Responsibilities
Convert DSP algorithms and build ML inference pipelines into efficient embedded C/C++ code for microcontrollers or other constrained platforms.
Optimize code for memory footprint, CPU usage, and real-time performance.
Collaborate with algorithm / ML researchers to refine models for embedded deployment.
Profile runtime behavior, identify bottlenecks, and perform low-level debugging.
Work with firmware teams to integrate algorithms into system software.
Develop monitoring and observability systems to track model performance, data drift, data quality, and overall system health.
Requirements
BS/MS in Electrical Engineering, Computer Engineering, Computer Science, or related field.
Strong proficiency in C/C++ for embedded systems.
Ability to read/translate algorithmic descriptions in Python/Matlab into low-level code.
Experience translating and optimizing machine learning models for embedded targets (e.g., quantization, fixed-point, pruning).
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