Edge AI Engineer
Tasks
- Build edge inference runtimes
- Build privacy respecting telemetry pipelines
- Collaborate with hardware, firmware, and product teams
- Design Edge AI solutions
- Design edge cloud hybrid architectures
- Develop benchmarking suites
- Evaluate on device privacy and bias
- Implement model compression and quantization
- Implement on device model update and rollback
- Implement secure execution and model integrity
- Maintain technical documentation and runbooks
- Optimize latency energy and memory
- Optimize models for accelerator backends
Perks/Benefits
- N/A
Skills/Tech-stack
C++ | Core ML | DSP | Edge inference | Embedded Systems | Energy Efficiency | Federated Learning | Knowledge Distillation | Latency optimization | Machine Learning | Mobile GPU | Mobile SoC | Model Compression | Model Pruning | Model Quantization | Model Rollback | Model versioning | NPU | ONNX Runtime | Privacy & Security | Python | Telemetry pipelines | TensorFlow Lite
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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