The work
Start from a recent software engineering paper with released code, ideally your own. Remove the implementation of the paper's core contribution, then package the remaining repository as a task in which an AI agent must reconstruct that contribution and outperform the published results on the paper's benchmarks.
Task design and review
You will write precise task statements, create held-out evaluation workloads, define pass thresholds for each metric and provide both a hidden reference solution and a second solution demonstrating that the target can be exceeded. After agents attempt the task, you will review their implementations and results. Relevant research depth includes test generation, program repair, static analysis and mining software repositories.
What the platform screens for
The screen focuses on verifiable publication history, released research code and a completed or in-progress PhD in computer science or a related field. Expect follow-up on experimental design, benchmark leakage, reproducibility and whether your proposed evaluation distinguishes genuine technical progress from benchmark-specific shortcuts. First-author work reporting measured improvements over a baseline, Docker experience and reproducible benchmark setups are preferred rather than required.
Logistics
The contract is fully remote, asynchronous and flexible. Each task typically takes a few hours, and candidates who meet the stated requirements and provide the requested paper and artifact materials are prioritised for review; the process also includes background checks.
Pay band: $80/hr
