SeniorAppliedScientist

Build the scientific intelligence layer powering Amazon’s satellite manufacturing system. We are looking for a Senior Applied Scientist to lead the development of models that transform fragmented manufacturing, test, quality, and operational data into a unified, closed-loop intelligence system that directly improves how satellites are built. You will work on high-ambiguity problems where data is incomplete, noisy, and distributed, and where model outputs directly influence real-world manufacturing decisions. Your work will power AI-native workflows such as non-conformance disposition, root-cause analysis, and predictive test optimization, reducing defects, accelerating production, and enabling self-improving manufacturing systems. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. Key job responsibilities In this role, you will design and deploy purpose-built models that power production-critical decisions across satellite manufacturing. - Lead the design, training, and deployment of machine learning models, including LLM-based systems, retrieval models, and task-specific models - Translate ambiguous, real-world manufacturing problems into well-defined scientific problems, modeling approaches, and evaluation criteria - Train, fine-tune, and evaluate models using large-scale, noisy, and heterogeneous datasets with incomplete or delayed ground truth - Develop models over partially observed systems spanning test data, inspection signals, quality records, supplier data, and knowledge systems - Invent and extend approaches for problems such as anomaly detection, root-cause inference, multimodal learning, and generative AI under real-world constraints - Define evaluation frameworks that capture real-world failure modes, distribution shift, and decision risk, and use them