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2 weeks ago
We are seeking an experienced computer vision researcher to join our team. The ideal candidate will have expertise in transformer-based models and deep learning fundamentals.
About the RoleThis is a challenging project that involves developing and implementing cutting-edge technology for semantic segmentation of aerial imagery. The role demands strong skills in model design, training, and optimization.
Key Responsibilities:- Design and implement transformer-based architecture for semantic segmentation of aerial imagery
- Develop efficient image-to-token and token-to-image conversion pipelines
- Create and maintain training datasets, including data cleaning, augmentation, and validation
- Optimize model training processes for distributed computing environments
- Implement efficient inference pipelines for production deployment
- Collaborate with engineering team to integrate new models into existing infrastructure
The successful candidate will have a strong foundation in computer vision and deep learning fundamentals. Experience with PyTorch and ONNX or TensorRT model optimization and deployment is essential. A deep understanding of distributed computing and parallel processing is also required.
What We Offer- A vast aerial imagery database (7 cm GSD) of 500,000+ properties across the U.S.
- A team of 60 annotators mapping thousands of acres daily
- A ready market of 350+ customers for immediate deployment
- Po
wful compute resources for rapid model training
This is an exciting opportunity to work on a challenging project that has real-world implications. If you are passionate about computer vision and deep learning, we encourage you to apply.
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2 weeks ago
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