We are seeking a highly skilled Photogrammetrist and Computer Vision Research Engineer or Scientist to join our team. This role combines advanced expertise in photogrammetry, 3D reconstruction, and algorithm development with practical engineering know‑how in modern computer vision systems. The ideal candidate will lead research initiatives, develop novel imaging and reconstruction methods, and build production‑ready solutions that extract reliable spatial information from visual data. Key Responsibilities • Design, implement, and optimize photogrammetric workflows for aerial, terrestrial, and multi‑sensor imagery. • Develop state‑of‑the‑art algorithms for 3D reconstruction, image matching, feature extraction, and multi‑view geometry. • Conduct applied research in computer vision, including deep learning approaches for perception, segmentation, and structure‑from‑motion. • Implement and analyze error propagation techniques, including uncertainty modeling, covariance estimation, and error budgeting for photogrammetric and computer‑vision products. • Develop and integrate object recognition capabilities, including classical CV approaches and deep‑learning‑based detection, classification, and semantic segmentation. • Build scalable pipelines for ingesting, processing, and visualizing large imagery datasets. • Collaborate with software engineering teams to deploy solutions into production environments. • Support new business capture activities, including meeting with customers, participating in technical discussions, responding to RFIs, developing technical content for proposals, and contributing to capture strategy. • Document findings, publish research results when appropriate, and present technical insights to internal and external stakeholders. • Mentor team members and contribute to the long‑term research strategy of the organization. Because this role involves a combination of collaborative/in-person and independent work, it will take the form of a hybrid work format, with time split between working onsite and remotely.