AI Model Evaluator (LLM & Agent Systems)
AI-Powered Summary
Job Description
Job Title: AI Model Evaluator (LLM & Agent Systems)
Employment Type: Contract (Minimum 2 weeks, with potential extension)
Location: Remote
Job Summary:
Join our customer's team as an AI Model Evaluator (LLM & Agent Systems) and play a pivotal role in shaping the future of generative AI and autonomous agents. You'll help benchmark, analyze, and assess cutting-edge AI systems in real-world scenarios, providing structured insights that drive improvements. This position is ideal for analytical professionals passionate about AI quality and real-world impact.
Key Responsibilities:
Evaluate outputs from large language models (LLMs) and autonomous agent systems against defined guidelines and rubrics
Review multi-step agent actions, including screenshots and reasoning traces, to determine accuracy and quality
Consistently apply evaluation standards, flagging edge cases and identifying recurring patterns or failure modes
Provide detailed, structured feedback to inform benchmarking, product evolution, and model refinement
Participate in calibration and alignment sessions to ensure consistent application of evaluation criteria
Work collaboratively to adapt to evolving scenarios and ambiguous evaluation situations
Document findings and communicate insights clearly both in writing and verbally to relevant stakeholders
Required Skills and Qualifications:
Demonstrated experience with LLM evaluation, AI output analysis, QA/testing, UX research, or similar analytical roles
Strong background in AI model evaluation, benchmarking, and applying rubric-based scoring frameworks
Exceptional attention to detail and sound judgement in ambiguous or edge-case scenarios
Proficiency in English (B2+ or equivalent) with excellent written and verbal communication skills
Ability to adapt quickly to evolving guidelines and work independently
Comfort with remote work and a commitment of at least 20 hours per week for the initial term
Analytical mindset with a focus on actionable, qualitative feedback
Preferred Qualifications:
Experience with RLHF, annotation workflows, or AI benchmarking frameworks
Familiarity with autonomous agent systems or workflow automation tools
Background in mobile apps or digital product evaluation processes