Edge AI Engineer
Tasks
- Apply quantization pruning and distillation
- Build cross platform inference runtimes
- Build privacy respectful telemetry pipelines
- Create technical documentation runbooks and diagrams
- Design Edge AI solutions
- Design hybrid edge cloud architectures
- Develop benchmarking suites for accuracy latency energy
- Evaluate bias and on device privacy
- Implement on device model update and rollback
- Optimize accelerator backends
- Optimize models for latency energy and memory
- Secure execution paths and model integrity
Perks/Benefits
Skills/Tech-stack
C++ | Core ML | DSP | Edge Computing | Federated Learning | Inference Optimization | Knowledge Distillation | Machine Learning | Mobile GPU | Mobile SoC | Model Compression | Model Deployment | NPU | ONNX Runtime | Performance Engineering | Profiling | Pruning | Python | Quantization | TensorFlow Lite
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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