Role Overview
You will work on applied AI systems that drive real security outcomes, not just benchmark scores. This role focuses on model quality, reliability, observability, and measurable impact for enterprise customers.
Responsibilities
- Fine-tune, evaluate, and improve LLM workflows for vulnerability triage
- Build data pipelines for training, evaluation, and feedback collection
- Work closely with security engineers to validate model outputs in real-world scenarios
- Define and monitor model quality, reliability, and production metrics
- Ship AI features safely using staged rollouts and appropriate controls
Must-Have Qualifications
- Production experience with machine learning systems
- Strong Python skills and a solid foundation in model evaluation
- Experience with prompt design, retrieval workflows, and LLM application patterns
- Ability to make practical tradeoffs between quality, latency, and cost
Nice-to-Have
- Experience with adversarial machine learning or secure AI systems
- Background in vulnerability management or cybersecurity operations
- Hands-on experience with vector databases and retrieval systems