Computer Vision Engineer
Tasks
- Build and operate end to end MLOps pipelines
- Build versioned auditable datasets
- Define deep learning objectives datasets release standards
- Develop train and benchmark depth estimation models
- Develop train and benchmark detection models
- Develop train and benchmark segmentation models
- Drive real and synthetic data collection campaigns
- Export and optimize models for ONNX and TensorRT
- Maintain experiment tracking and reproducible training
- Set evaluation and failure analysis procedures
- Set up CI CD for model release
- Validate accuracy and runtime performance
Perks/Benefits
- Corporate benefits
- Equity options
- Flexible hours
- Learning opportunities
- Relocation support
- Remote options
Skills/Tech-stack
Annotation Validation | CI/CD | CNN | Computer Vision | Convolutional Neural Networks | Data Annotation | Data Annotation Validation | Data Versioning | Dataset Splitting | Depth Estimation | Experiment tracking | Image Segmentation | MLOps | NVIDIA Jetson | Neural Networks | ONNX | Object Detection | PyTorch | Python | TensorRT | Transformers
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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