Experience Requirements:

• 4+ years building ML solutions at scale

• Strong Python; deep experience with PyTorch/TensorFlow

• Hands-on distributed systems experience (Ray highly valued)

• Understanding of LLM orchestration, memory, retrieval, and planning

• Experience with MLOps/model versioning and experiment tracking (e.g., MLflow, DVC, Weights & Biases)

Other Requirements:

• Active TS/SCI clearance

• Builder's mindset

• Experience working with cyber/network telemetry or security datasets is a plus

• Familiarity with model security/adversarial ML

• Ability to identify and mitigate vulnerabilities

Responsibilities:

• Architect, train, and deploy AI systems for reasoning, planning, and multi‑step decision‑making

• Build and scale distributed training/inference pipelines using Ray and modern cloud infrastructure

• Integrate agentic AI into operational environments across cross‑functional teams

• Prototype techniques from memory‑augmented models to tool‑use orchestration

• Develop ML models on cyber data to support object detection, data triage, search/optimization, inference, behavior detection, and automated discovery and decision making