AI/ML Engineer
Tasks
- Build model registry
- Co register and stitch imagery
- Deploy models to production
- Develop MLOps pipeline
- Fine-tune computer vision models
- Handle large spatial context models
- Implement experiment tracking
- Integrate models into product
- Iterate training runs
- Manage dataset versioning
- Perform error analysis
- Run dataset curation and augmentation
- Set up monitoring in production
- Train computer vision models
Perks/Benefits
Skills/Tech-stack
Active Learning | Computer Vision | Data Augmentation | Dataset versioning | Deep learning | Experiment tracking | Image Segmentation | Keypoint Estimation | Keypoint detection | MLOps | Machine Learning | Model Deployment | Model Registry | Multi-scale Modeling | Object Detection | Production Monitoring | Python | Remote Sensing | Scale modeling | Self-Supervised Learning | Self-supervised | Supervised Learning | Weakly-Supervised Learning
Education
N/A
Roles
AI | AI/ML Engineer | Engineer | Learning Engineer | ML Engineer | Machine Learning Engineer
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