Edge AI Engineer
Tasks
- Apply model quantization pruning distillation
- Build inference runtimes
- Build telemetry pipelines
- Collaborate with hardware, firmware, and product teams
- Conduct privacy and bias evaluation
- Design Edge AI solutions
- Design hybrid edge cloud architectures
- Develop benchmarking suites
- Implement model update versioning rollback
- Implement secure execution and integrity verification
- Maintain technical documentation
- Optimize accelerator backends
- Optimize latency energy efficiency memory
- Translate edge AI advances into recommendations
Perks/Benefits
- N/A
Skills/Tech-stack
C plus plus | Core ML | Data Privacy | Edge Cloud | Edge Computing | Energy Efficiency | Federated Learning | Hybrid Edge Cloud | Inference Runtime | Integrity verification | Latency optimization | Machine Learning | Model Benchmarking | Model Compression | Model Distillation | Model Pruning | Model Quantization | ONNX Runtime | On Device Personalization | Performance Profiling | Python | Secure execution | Telemetry pipelines | TensorFlow Lite
Education
Roles
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