EBIT
Freelance / Remote (Indonesia)Current Role
Contribute to training and evaluating large language models by solving programming tasks, reviewing AI-generated code, developing test cases, and designing benchmark tasks for agentic software engineering evaluation.
Associated Projects
These projects are linked from the project workbook's Associated With column.
Designed and implemented production-grade software engineering benchmarks used to evaluate autonomous coding agents across realistic development environments and automated testing pipelines.
+6Designed and evaluated multi-agent AI workflows using OpenClaw to benchmark reasoning, planning, debugging, tool orchestration, and software engineering capabilities of large language models.
+10Role Detail
Responsibilities pulled from the professional experience workbook and tightened into recruiter-readable evidence.
Evaluated AI-generated code for correctness, efficiency, readability, and adherence to task requirements.
Solved algorithmic and software engineering problems across multiple programming languages.
Developed comprehensive test cases to validate functionality, edge cases, and code robustness.
Provided clear technical explanations and human-readable rationales for evaluation decisions.
Identified logical errors, performance issues, and opportunities to improve AI-generated solutions.
Collaborated on annotation and evaluation workflows to enhance LLM coding performance and reliability.
Designed reproducible benchmark tasks, validation pipelines, and scoring workflows for agentic AI software engineering evaluations.
