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Specialized geospatial ML lead role in metro market with mid-level experience requirement.
Highly domain-specific geospatial ML and Earth Observation expertise reduces cross-industry transferability.
Multiple explicit mandates: PhD/MS preference, 6+ years, 2+ leadership, production ML and MLOps required.
Lead multiple machine learning and computer vision initiatives for geospatial intelligence applications across domains like agriculture, forestry, and climate.
Own end-to-end delivery of large-scale ML systems including problem framing, data design, model development, deployment, and monitoring.
Lead and mentor technical teams, collaborate cross-functionally, drive experimentation, and communicate findings to leadership and external partners.
PhD/M.Tech/MS (Research) in CS, EE, EC, Remote Sensing, or related fields; exceptional undergraduates with strong experience considered.
6+ years of applied ML/Computer Vision experience in industry preferred.
2+ years in technical leadership role involving people and project management.
Proven expertise with Transformers, PyTorch, Python, distributed systems, and deployment of production ML models.
Experienced in advancing geospatial ML/CV state-of-the-art, handling ambiguity and scaling solutions across geographies and sensors.
Strong track record in research or industry with ability to innovate model architectures including generative and temporal models.
Capable of leading technical teams while managing complex projects and contributing to organizational knowledge via patents or publications.