Edge AI Engineer
Tasks
- Apply quantization pruning distillation model optimization
- Build cross platform edge inference runtimes
- Build privacy preserving telemetry pipelines
- Design and implement Edge AI solutions
- Design hybrid edge cloud architectures
- Develop benchmarking suites for accuracy latency and energy
- Implement on device model update versioning and rollback
- Implement secure execution paths model protection and integrity verification
- Maintain technical documentation and runbooks
- Optimize models for accelerator backends
- Perform responsible AI privacy and bias evaluation
- Tune model performance for latency energy and memory
Perks/Benefits
- N/A
Skills/Tech-stack
C++ | Core ML | Data Security | Embedded Systems | Federated Learning | Hardware Architecture | Hardware optimization | Hybrid Cloud | Integrity verification | Knowledge Distillation | Machine Learning | Mobile Hardware | Mobile Hardware Architecture | Model Benchmarking | Model Compression | ONNX Runtime | On Device Privacy | Performance Profiling | Pruning | Python | Quantization | TensorFlow Lite
Roles
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