Edge AI Engineer
Tasks
- Apply quantization pruning distillation
- Build edge inference runtimes
- Build privacy preserving telemetry pipelines
- Collaborate with hardware, firmware, and product teams
- Conduct bias evaluation and responsible AI
- Design Edge AI solutions
- Design hybrid edge cloud architectures
- Develop benchmarking suites
- Implement on device model update versioning rollback
- Implement secure execution model protection integrity
- Maintain technical documentation and runbooks
- Optimize accelerator backends
- Translate edge AI hardware updates into adoption recommendations
- Tune latency energy and memory performance
Perks/Benefits
Skills/Tech-stack
By Design | C++ | Core ML | Device deployment | Edge Cloud | Edge inference | Energy optimization | Federated Learning | Hybrid Edge Cloud | Integrity verification | Knowledge Distillation | Latency optimization | Machine Learning | Memory Optimization | Model Benchmarking | Model Compression | ONNX Runtime | On-device Deployment | Performance Profiling | Privacy by Design | Pruning | Python | Quantization | Security | TensorFlow Lite
Education
Roles
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