Senior Applied Scientist, Leo Security

What you'll do

• Build production-grade neurosymbolic systems, graph-based reasoning, and LLM agents for security outcomes.
• Develop and evaluate reinforcement learning, fine-tuning, and behavioral detection models; build multi-agent workflows for security-event response.
• Lead the research-to-production science lifecycle, define impact metrics, and contribute through publications, patents, or open-source work.

What they ask for

• 3+ years of experience building machine learning models for business applications.
• PhD, or a Master's degree and 6+ years of applied research experience.
• Programming experience in Java, C++, Python, or a related language; experience with neural deep learning methods and machine learning.
• Experience with graph algorithms, knowledge graphs, unsupervised learning, NLP, embedding-based retrieval, and evaluation frameworks for AI systems requiring human judgment.

Nice to have

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, or scipy.
• Experience in security domains, large-scale stream processing, LLM cost and latency optimization, or relevant publications.

Pay

167,100.00 - 226,100.00 USD annually (base salary), USA, VA, Arlington; 167,100.00 - 226,100.00 USD annually (base salary), USA, VA, Herndon; 167,100.00 - 226,100.00 USD annually (base salary), USA, WA, BELLEVUE

Tools

Java, C++, Python, GRPO, PPO, DPO, R, scikit-learn

AI focus

Develops neurosymbolic reasoning systems, LLM agents, reinforcement learning and fine-tuning pipelines, behavioral detection models, and multi-agent security response workflows.