Staff Machine Learning Engineer
Tasks
- Apply graph level operator fusion
- Build data processing and versioning pipelines
- Collaborate with silicon teams on NPU and FPGA architecture
- Design autonomous agents for resource constrained edge devices
- Design end to end MLOps architecture
- Develop computer vision capabilities
- Develop custom operators
- Develop on device monitoring for inference quality and concept drift
- Implement edge model security and verification framework
- Implement human in the loop and active learning labeling systems
- Integrate secure model authentication and entity verification
- Optimize models for NPU and hardware inference engine
- Perform real-time log analysis
- Prevent model injection
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Active Learning | Apache TVM | Argo | Azure | C++ | CI/CD | Computer Vision | Custom ops | Data Versioning | Device Monitoring | GCP | GPU scheduling | Graph optimization | Human-in-the-loop | Kubeflow | Kubernetes | LLMs | Log Analysis | MLIR | MLOps | Model Security | Model signing | On Device Monitoring | Operator fusion | PyTorch | Python | RISC-V | Rust | Secure Communication | TensorFlow | The Loop | Transformers | VHDL | Verilog | Virtualization | Yocto
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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