AI QA

任职要求

<p><strong>Core Responsibilities</strong></p><p>· <strong>AI Quality Assessment Framework &amp; Standards</strong></p><p>o Establish and maintain quality evaluation criteria for Large Language Models (LLMs), covering accuracy, safety, compliance, and instruction-following capabilities.</p><p>o Design evaluation workflows combining automation and human-in-the-loop assessment to quantify model performance regularly.</p><p>· <strong>End-to-End Quality Control &amp; Risk Management</strong></p><p>o Own regression testing and acceptance testing for model iterations, enforcing quality gates to prevent performance degradation before launch.</p><p>o Monitor online performance to mine for badcases, identifying model hallucinations, logic errors, or experience defects, and issue timely risk alerts.</p><p>· <strong>Issue-Driven Improvement &amp; Closed-Loop Management</strong></p><p>o Lead Root Cause Analysis (RCA) for quality issues, precisely diagnosing whether failures stem from data, prompts, or model architecture.</p><p>o Drive algorithm, product, and operations teams to resolve quality defects, track the fix rate and conduct re-validation to ensure a closed-loop process.</p><p>· <strong>Cross-functional Collaboration</strong></p><p>o Bridge the gap between business needs and technical implementation, ensuring the AI delivers real value to users.</p><p><br></p><p><strong>Key Qualifications and Experience</strong></p><p>· <strong>Educational Background: </strong>Full-time bachelor's degree or higher.</p><p>· <strong>Work Experience: </strong>3+ years of experience in internet product operations. Hands-on experience in LLM/AIGC product operations is highly preferred.</p><p>· <strong>Professional Skills: </strong></p><p>o Mastery of AI evaluation methodologies (e.g., Golden Dataset construction, Human Evaluation SOPs).</p><p>o Sharp eye for detail ("bug hunting" mindset) with the ability to mine potential risks from massive data.</p><p>o Familiarity with Prompt Engineering to reproduce or verify issues (focus on validation rather than daily maintenance).</p><p>· <strong>Soft Skills: </strong>Strong cross-functional communication skills; ability to use data to influence and drive cross-functional partners to solve complex problems.</p><p>· <strong>Language Skills: </strong>Proficiency in written and spoken English.</p><p>· <strong>Preferred Qualifications: </strong>Project management experience is a plus.</p>