Machine Learning Engineer

• Architect and lead development of large-scale evaluation platforms for LLMs and agents, enabling automated, reproducible, and extensible assessment
• Define organizational standards and metrics for LLM/agent evaluation covering hallucination detection, factuality, bias, robustness, interpretability, and alignment drift
• Build platform components and APIs to allow product teams to integrate evaluation into training, fine-tuning, deployment, and continuous monitoring workflows
• Design automated pipelines and benchmarks for adversarial testing, red-teaming, and stress testing of LLMs and RAG systems
• Lead initiatives in multi-dimensional evaluation including safety, grounding, and agent behaviors
• Collaborate with cross-functional stakeholders to translate evaluation goals into measurable system-level frameworks
• Advance interpretability and observability tooling to understand, debug, and explain LLM behaviors in production
• Mentor engineers and establish best practices driving adoption of evaluation-driven development
• Influence technical roadmaps and represent the team’s evaluation-first approach in external forums and publications

Principal ML Engineer

Senior Data/AI Engineer

Senior Software Engineer – Secure Cloud, AI Engineering Systems

Machine Learning Engineer

Staff Machine Learning Engineer, Listings and Host Tools – Data and AI

Machine Learning Engineer 5 – Ads