Computer Vision Engineer

• Design and improve training pipelines to support faster, continuous model iteration
• Enable scalable experimentation across datasets, model architectures, and training strategies
• Improve reproducibility, experiment tracking, and comparison of training runs
• Build and refine workflows for: Data indexing, curation, and preprocessing
• Label quality validation and dataset management
• Data exploration for targeted labeling
• Develop evaluation and tests that reflect real-world operating conditions
• Improve synthetic data workflows to support targeted model improvement
• Train, evaluate, and iterate on computer vision models for: Detection, segmentation, classification, tracking
• Continuously explore and evaluate: new model families and research directions
• Incorporate multi-modal inputs including: Multiple image bands, Platform and sensor metadata (range, angles, telemetry, etc.)
• Optimize models for deployment on embedded GPU platforms like Nvidia Jetson
• Balance accuracy, latency, and resource constraints for real-world, real-time workflows

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Senior Machine Learning Engineer, Computer Vision