Computer Vision AI & ML Engineer
Tasks
- Automate performance reporting
- Build automated annotation workflows
- Build data processing pipelines
- Build evaluation pipelines
- Build training pipelines
- Deploy machine learning models to production
- Design data labeling strategies
- Develop deep learning models for 3D scene understanding
- Develop deep learning models for object detection
- Develop deep learning models for segmentation
- Develop deep learning models for tracking
- Implement failure detection
- Implement monitoring and reliability frameworks
- Implement uncertainty estimation
- Integrate perception models into production pipelines
- Run proof-of-concept experiments
Perks/Benefits
- N/A
Skills/Tech-stack
3D Geometry | 3D Scene | 3D Scene Understanding | Blender | Computer Vision | Data Augmentation | Data labeling | Dataset Management | Dataset versioning | Deep learning | Evaluation Frameworks | Failure Detection | Gazebo | Isaac Sim | JAX | Lidar | MLOps | Machine Learning | Machine learning deployment | Monitoring | Multi Sensor | Multi-sensor Fusion | Object Detection | PyTorch | Python | RGB-D | Real Time | Real-time Systems | Scene Understanding | Segmentation | Sensor fusion | Simulation | Stereo vision | TensorFlow | Time Systems | Tracking | Training pipelines | Uncertainty Estimation
Education
N/A
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