Edge AI Engineer
Tasks
- Apply quantization pruning distillation and model compression
- Build cross platform inference runtimes
- Build privacy preserving telemetry pipelines
- Collaborate with hardware, firmware, and product teams
- Design edge AI solutions optimized for hardware
- Design hybrid edge cloud architectures with graceful degradation
- Develop benchmarking suites for accuracy latency and energy
- Implement on device model update versioning and rollback
- Implement secure execution and model protection
- Maintain technical documentation
- Optimize latency energy efficiency and memory footprint
- Optimize models for accelerator backends
- Perform bias evaluation and privacy checks
- Translate edge AI hardware and software updates into recommendations
Perks/Benefits
- N/A
Skills/Tech-stack
Benchmarking | Bias Evaluation | C++ | Core ML | Device security | Edge AI | Energy optimization | Federated Learning | Hybrid Cloud | Integrity verification | Knowledge Distillation | Latency optimization | Machine Learning | Memory Footprint | Memory Footprint Optimization | Model Compression | Model protection | ONNX Runtime | On-device security | Performance Profiling | Pruning | Python | Quantization | Secure execution | Telemetry pipelines | TensorFlow Lite
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