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Senior Applied Scientist, Leo Security

Amazon· Applied Science
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Arlington, VA, Herndon, VA, Bellevue, WA$167.1k - $226.1kUnknownPosted yesterday

About the role

Senior Applied Scientist on the Engineering and R&D team for Leo Space Security, building neurosymbolic reasoning platforms and models to detect and contain threat actors across the Leo satellite constellation security infrastructure.

Responsibilities

  • - Design and implement scalable, production-grade neurosymbolic systems that integrate symbolic reasoning over graph-based knowledge representations with LLM agents to deliver reliable, verifiable security outcomes.
  • “- Design and run reinforcement learning and fine-tuning pipelines (GRPO, PPO, DPO) to optimize language models for security reasoning, triage, and detection-authoring tasks.
  • - Build behavioral and statistical models that detect threat actor behavior, and design evaluation frameworks that measure model performance before production use.
  • - Design and build multi-agent systems that autonomously triage, enrich, and contain security events, including constrained reasoning, safety guardrails, and validation mechanisms for trustworthy automated decisions.
  • - Own the end-to-end science lifecycle, from research and experimentation through production deployment, defining metrics that measure system performance and real-world security impact.
  • - Advance the state of the art through publications, patents, or open-source contributions and shape the scientific agenda from day one.

Qualifications

  • - 3+ years of building machine learning models for business applications
  • - PhD, or Master's degree and 6+ years of applied research experience
  • - Experience programming in Java, C++, Python or related language
  • - Experience with neural deep learning methods and machine learning
  • - Experience with graph algorithms, knowledge graphs, unsupervised learning (clustering, dimensionality reduction, anomaly detection), NLP, and embedding-based retrieval
  • - Experience designing evaluation frameworks for AI systems with ground truth requiring human judgment, including staged rollouts, A/B testing, and expert feedback loops

Skills

Required:Machine learning model developmentReinforcement learningGraph-based reasoningNLP and embedding retrievalEvaluation frameworks for AI systems
Last updated Oct 25, 2026. Interested? Apply on the company site.

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