Applied AI Engineer II
Tasks
- Build automated MLOps workflows and pipelines
- Collaborate on APIs and microservice protocols
- Deploy and serve models using containerized edge inference
- Design edge device ML and computer vision applications
- Ensure observability security logging and alerting
- Interface ML pipelines with data validation and feature engineering
- Optimize real time performance and pipeline output
- Own ML and computer vision components
- Refactor and harden AI models for production
- Translate research results into production systems
Perks/Benefits
- N/A
Skills/Tech-stack
Bash | CI/CD | Computer Vision | Docker | Edge Computing | Git | GitLab CI | GitLab CI/CD | Latency Tuning | MLOps | Machine Learning | Microsoft Azure | Model Optimization | ONNX | OpenCV | Pruning | PyTorch | Python | Quantization | TensorRT | Video Processing | Video Streaming | Video decoding
Education
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