Search Results for "Ncover"

The Senior AI Evaluation Engineer designs, implements, and operationalizes robust evaluation systems to measure the quality, safety, reliability, and business performance of AI models—especially modern ML and LLM-based capabilities—throughout the development lifecycle and in production. The role translates ambiguous “model quality” questions into measurable metrics, repeatable test suites, and automated gates that prevent regressions and enable responsible scaling of AI features.

The **Model Validation Engineer** is an individual contributor engineering role responsible for independently assessing, testing, and challenging machine learning (ML) models before and after deployment to ensure they are accurate, robust, explainable, and safe for production use. This role designs and executes validation methodologies (offline evaluation, bias/fairness checks, stress testing, drift monitoring, and reproducibility verification) and translates findings into actionable engineering and product decisions.

The **AI Red Team Engineer** proactively identifies, validates, and helps mitigate security, safety, and misuse risks in AI systems—especially **LLM-powered products**, AI agents, and ML-enabled features—before those risks impact customers or the business. The role blends adversarial engineering, applied security testing, and practical ML/LLM understanding to uncover failure modes such as jailbreaks, prompt injection, data leakage, harmful content generation, and tool/agent misuse.