Senior Applied Scientist, Leo Security
Core
Founding Applied Scientist building neurosymbolic reasoning platforms and agentic AI systems to detect sophisticated threat actors and secure global satellite infrastructure.
Role type
Senior Applied Scientist (Security R&D)
Builds
Neurosymbolic reasoning platforms, multi-agent security systems, and detection models for satellite constellation defense
Domain
Space infrastructure security, agentic AI, graph-based reasoning
Deliverable
production ML models
Required skills
neurosymbolic reasoning, reinforcement learning (GRPO, PPO, DPO), graph algorithms, knowledge graphs, unsupervised learning, NLP, embedding-based retrieval, evaluation framework design
Preferred skills
terabyte-scale stream processing, LLM cost/latency optimization, security architecture modeling, quantitative solution design, publications in applied ML/security
Technologies
Java, C++, Python, Tensorflow, numpy, scipy, Spark MLLib, MxNet, scikit-learn
Responsibilities
Design scalable neurosymbolic systems integrating symbolic reasoning with LLM agents; build behavioral models to detect threat actor behavior; design multi-agent systems for autonomous security event triage; own end-to-end science lifecycle from research to production; advance state of the art via publications and patents
Seniority
Senior, hands-on IC with research mandate
