AI Safety Research Engineer

You will build automated evaluation infrastructure for frontier large models and AI agent systems. You will integrate models, benchmarks, and harnesses; develop safety products; optimize platform performance and reliability; and deploy safety services for client AI systems.

Responsibilities

• Build automated evaluation platforms for large models, multimodal models, harnesses, AI agents, and multi-agent systems
• Develop model integration, benchmark integration, harness integration, request routing, task scheduling, error handling, cost optimization, and data analysis capabilities
• Integrate open-source and in-house benchmarks
• Ensure platform feature completeness, result accuracy, and operational stability
• Productize AI safety evaluation, risk modeling, alignment, and monitoring technologies
• Optimize product functionality, performance, usability, and stability
• Deploy safety products as services for large-model and AI-agent developers
• Provide implementation plans, evaluation reports, vulnerability assessments, and improvement recommendations

Requirements

• Bachelor’s degree or above
• Python
• Data structures and algorithms
• Linux CLI
• Git
• Docker
• Kubernetes
• Large-model API integration
• Model deployment
• Benchmarking
• Technical documentation
• Chinese reading, writing, and spoken communication