Staff Embedded ML Engineer, Edge AI
Core
Lead on-device inference and performance optimization of ML models for outdoor monitoring in home security cameras and doorbells.
Role type
Staff Embedded ML Engineer (Edge AI)
Builds
Real-time video/event pipelines on embedded hardware (outdoor cameras, doorbells)
Domain
Home Security / Edge AI / Embedded Systems
Deliverable
production ML models
Required skills
C/C++, embedded systems, low-level performance optimization, ML inference optimization, kernel/operator tuning, profiling/debugging, cross-functional leadership
Preferred skills
SIMD (ARM NEON/SVE), quantized inference (INT8), embedded accelerators (DSP/NPU/GPU), camera/doorbell pipelines, OS/firmware constraints, security/privacy for edge devices
Technologies
TFLite, ONNX Runtime, TensorRT, C/C++, SIMD, INT8, ARM NEON/SVE
Responsibilities
Own embedded deployment and performance of on-device ML inference; Optimize end-to-end inference across CPU/DSP/NPU/GPU; Perform kernel/operator-level optimization; Integrate and maintain ML models within embedded pipelines; Drive quantization and deployment readiness; Build tooling for profiling and benchmarking; Provide Staff-level leadership
Seniority
Staff, hands-on IC with mentorship
