Staff Embedded ML Engineer, Edge AI
Tasks
- Build tooling for profiling benchmarking and regression tracking
- Drive quantization and deployment readiness
- Integrate and maintain ML models in embedded pipelines
- Lead technical reviews mentor engineers and set performance standards
- Optimize end to end inference performance
- Own embedded on device ML inference
- Perform kernel operator level optimization
- Translate model changes into deployment impact
Perks/Benefits
- Employee Resource Groups (ERGs)
- Free home security system
- Hybrid work model
- Professional monitoring
- Wellness and lifestyle benefits
Skills/Tech-stack
ARM NEON | Bandwidth Optimization | C# | C++ | Cache optimization | Computer Vision | DMA | Debugging | Embedded Linux | FP16 | Flame Graphs | Hardware counters | INT8 | Kernel optimization | Machine Learning | Memory Optimization | Memory bandwidth | Memory bandwidth optimization | Model Quantization | ONNX Runtime | Operator optimization | Performance Benchmarking | Profiling | Real Time | Real-time Systems | Regression testing | SIMD | SIMD optimization | SIMD vectorization | Secure boot | TEE | TFLite | TensorFlow Lite | TensorRT | Thread scheduling | Time Systems | Tracing | Video Processing | Zero copy
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Regions
Countries
States
Cities
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