Edge AI Engineer
Tasks
- Apply quantization pruning distillation model optimization for edge constraints
- Build cross platform inference runtimes
- Build privacy preserving telemetry pipelines
- Collaborate with hardware, firmware, and product teams
- Create technical documentation and runbooks
- Design edge AI solutions optimized for target hardware
- Design hybrid edge cloud architectures with connectivity degradation
- Develop benchmarking suites for accuracy latency and energy tradeoffs
- Implement on device model update versioning and rollback workflows
- Implement secure execution model protection and integrity verification
- Optimize models for accelerator backends DSP NPU and mobile GPU
- Perform responsible AI evaluation for privacy and bias
- Tune model performance for latency energy efficiency and memory
Perks/Benefits
Skills/Tech-stack
C++ | Core ML | Energy Efficiency | Federated Learning | Knowledge Distillation | Latency optimization | Machine Learning | Model Benchmarking | Model Compression | Model Security | ONNX Runtime | Performance Tuning | Pruning | Python | Quantization | Telemetry | TensorFlow Lite | Version control
Education
Roles
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