Edge AI Engineer
Tasks
- Apply quantization pruning distillation and architectural optimization
- Build cross platform inference runtimes
- Build privacy preserving telemetry pipelines
- Conduct responsible AI privacy and bias evaluation
- Design and implement Edge AI solutions
- Design hybrid edge cloud architectures
- Develop benchmarking suites
- Implement on device model update versioning and rollback
- Maintain technical documentation and operational runbooks
- Optimize models for accelerator backends
- Secure model execution paths and integrity verification
- Tune model performance for latency energy efficiency and memory
Perks/Benefits
- N/A
Skills/Tech-stack
Benchmarking | C++ | Core ML | Device security | Energy optimization | Federated Learning | Integrity verification | Knowledge Distillation | Latency optimization | Machine Learning | Memory Optimization | Model Compression | Model Deployment | ONNX Runtime | On Device Privacy | On-device security | Performance Profiling | Pruning | Python | Quantization | Secure execution | Telemetry pipelines | TensorFlow Lite
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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