Responsibilities
- Help create computer vision systems to detect and identify wildfire smoke
- Support development of models that detect and categorize vegetation types
- Contribute to building models for identifying and recognizing infrastructure and assets
- Assist in designing computer vision solutions for instance-level segmentation tasks
- Work on semantic segmentation models to interpret visual scenes
- Support implementation and upkeep of machine learning and computer vision workflows
- Help deploy and fine-tune AI models on edge computing platforms such as NVIDIA Jetson
- Participate in optimizing model performance through techniques like TensorRT, quantization, and inference speed-ups
- Develop software tools for handling data, visualizing outputs, and measuring system performance
- Run tests, assess model accuracy, and communicate results to technical teams
- Troubleshoot problems related to model inference, device networking, and hardware integration
- Support processes that improve model training through ongoing data evaluation and feedback loops
- Work with AI researchers, software and hardware engineers, and product staff to align technical development
- Record experimental outcomes, technical choices, and established best practices
- Tackle diverse technical problems and grow expertise across computer vision and cloud-to-edge AI systems
Benefits
- Equity is offered for standard full-time positions
- Health insurance aligned with local laws and regional norms
- Retirement or pension contributions based on local standards
- Paid leave policies adjusted to regional requirements
Compensation
Final pay is based on candidate qualifications, education, experience, skills, knowledge, and geographic location
Work Arrangement
Hybrid
Team
North America, Australia
Other
- Final compensation determined by qualifications, education, experience, skills, knowledge, and geographic location
- Benefits vary by country of employment and include health coverage, retirement or pension contributions, and paid time off
