Research Engineer - Computer Vision

Key Responsibilities: Model Evaluation & Ground Truth Systems Own the evaluation definitions, metrics, and ground truth standards for computer vision systems operating on satellite imagery. Design and maintain benchmark datasets and evaluation protocols for tasks such as: Object detection Change detection Segmentation Geospatial feature extraction Ensure evaluation frameworks reflect real-world geospatial use cases and edge cases. Evaluation Infrastructure Build and maintain evaluation harnesses that automatically run experiments across models and datasets. Publish experiment results to a centralized system (e.g., Weights & Biases or similar experiment tracking tools).Develop reproducible pipelines that enable researchers to compare model performance across versions and datasets. Internal Tooling & Dashboards Develop lightweight internal tools and dashboards that allow engineers and researchers to: Inspect model outputs Compare predictions vs. ground truth Explore dataset slices Debug failure modes Build review and triage systems that streamline model analysis workflows for CV researchers. Applied Computer Vision Research Support Collaborate with research teams to analyze model performance on high-resolution satellite and aerial imagery. Help identify systematic failure modes and propose evaluation-driven improvements. Support experimentation with state-of-the-art CV models including foundation models, segmentation networks, and geospatial ML architectures. Cross-Team Impact Establish best practices for evaluation and ML experimentation across the organization. Provide technical leadership in reproducibility, benchmarking, and model validation. Mentor engineers and researchers in designing reliable evaluation systems.