Senior Applied Computer Vision Engineer
Tasks
- Analyze failure modes
- Build dataset creation and augmentation pipelines
- Collaborate with cross-functional engineering teams
- Define evaluation metrics and testing strategies
- Deploy machine learning solutions to production
- Design camera calibration solutions
- Develop production computer vision models for sports video analytics
- Estimate homography
- Evaluate computer vision pipelines
- Implement event recognition
- Implement identity association
- Implement multi-object tracking
- Implement object detection
- Implement quality assurance processes
- Lead technical initiatives from prototyping to deployment
- Map image coordinates to real world environments
- Monitor model performance in production
- Optimize inference performance
- Perform field registration
- Train and fine-tune deep learning models
Perks/Benefits
- Coworking space option
- Flexible working hours
- Fully remote
- Home office equipment allowance
- No business travel required
- Paid sick leave
- Paid vacation
- Technical growth opportunities
- Work/life balance focus
Skills/Tech-stack
Camera Calibration | Cloud infrastructure | Coordinate mapping | Data Augmentation | Deep learning | Domain Adaptation | Event recognition | Experiment tracking | Fine Tuning | GPU Computing | Homography Estimation | Identity Association | Image Coordinate Mapping | Inference Optimization | MLOps | Machine Learning | Model Fine-tuning | Monitoring | Multi-object Tracking | Object Detection | Object Tracking | Projective geometry | PyTorch | Python | Transfer Learning | Video Analytics
Education
N/A
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