Staff Applied AI Engineer

Advanced degree in Computer Science, Artificial Intelligence, Remote Sensing, or similar 12+ years expertise (or demonstrably equivalent) in Computer Science, Artificial Intelligence, Remote Sensing, or a related field Experience with remote sensing, satellite image analysis, and geospatial data Experience with rapid prototyping of AI Applications, especially search, LLMs, and agents Extensive experience in developing and deploying AI/ML models, with a focus on geospatial applications and foundation models, embeddings, and frontier VLLMs Excellent understanding of generative AI techniques, including LLMs and embeddings Proficient in Python and deep learning frameworks and high-performance distributed computing and IO frameworks using the python ecosystem Expertise with computer vision and natural language processing techniques and familiarity with joint multimodal embeddings generators like CLIP Familiarity with multi-dimensional geometry, statistics, linear algebra, optimization, and deep learning architectures Fluency in full stack-development development and effective GUI implementation for web applications Knowledge of geospatial data formats and analysis tools Excellent problem-solving skills Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and big data workflows Excellent communication and collaboration skills Experience with distributed computing (Docker/K8s, Dask, Ray Serve)

Develop and optimize multimodal LLM applications Build embedding & similarity search pipelines at planetary scale Fine‑tune multimodal foundation models for Earth‑observation tasks Design and execute machine learning workflows for geospatial analysis Define success criteria and model benchmarks Co‑design tool schemas & guardrails with backend engineers Collaborate with research scientists and engineers Automate preprocessing and labeling geospatial data Evaluate and improve algorithms for feature detection and classification Publish findings internally & externally