Edge AI Engineer
Tasks
- Apply model compression and quantization
- Build cross platform inference runtimes
- Build privacy preserving telemetry pipelines
- Collaborate with hardware and firmware teams
- Design Edge AI solutions
- Design hybrid edge cloud architectures
- Develop benchmarking suites
- Evaluate responsible AI including privacy and bias
- Implement on device model update and rollback
- Maintain technical documentation
- Optimize latency energy and memory
- Secure model execution and integrity verification
- Stay current with edge AI hardware and software
- Tune accelerator backend performance
Perks/Benefits
- N/A
Skills/Tech-stack
C++ | Core ML | DSPs | Edge Cloud | Edge inference | Energy Efficiency | Federated Learning | Hybrid Edge Cloud | Integrity verification | Knowledge Distillation | Latency optimization | Machine Learning | Memory Optimization | Mobile GPUs | Mobile SoCs | Model Compression | Model Integrity | Model Integrity Verification | Model Optimization | NPUs | ONNX Runtime | Performance Profiling | Privacy & Security | Pruning | Python | Quantization | TensorFlow Lite
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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