Design a Capability Evaluation for an Open-Weights Coding Model
Overview
What this challenge is about.
Design a Capability Evaluation for an Open-Weights Coding Model. Advanced challenge in research. Conducting rigorous research on real questions, earn a block...
The Brief
What you'll do, and what you'll demonstrate.
Run a documented capability evaluation of an open-weights coding model across benign, dual-use, refusal-bait, and hard buckets.
This is not a research exercise. It is the work a researcher does to produce findings that withstand scrutiny. That distinction matters to every hiring manager who has seen candidates summarize papers and none who have produced original findings under expert review.
When you finish, you will have something most graduates do not: a real-world deliverable, verified by Ewance, that you can show to a hiring manager and say "I did this. Here is the proof."
Earning criteria — what you'll demonstrate
- Design a multi-bucket capability evaluation with refusal tracking
- Use only public, ethics-safe task sources for dual-use buckets
- Report capability results with statistical honesty
- Translate evaluation results into policy-relevant observations
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
AI Safety and Alignment
Master · Responsible Ai
Strong alignment
This challenge maps to AI Safety and Alignment at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Capability Evaluation
Apply capability evaluation to solve real industry problems and demonstrate production-level capability.
- Safety Evaluation
Apply safety evaluation to solve real industry problems and demonstrate production-level capability.
- Llm Evaluation
Apply llm evaluation to solve real industry problems and demonstrate production-level capability.
- Research Writing
Apply research writing to solve real industry problems and demonstrate production-level capability.
- Policy Communication
Apply policy communication to solve real industry problems and demonstrate production-level capability.
- Python
Write clean, efficient Python for data processing, automation, and backend services.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
AI Safety Researcher
Public capability evaluations with policy framing are exactly the role's contribution to the AI governance conversation.
This challenge sharpens
- capability-evaluation
- safety-evaluation
- policy-communication
ML Researcher
Designing a multi-bucket evaluation set with rigorous statistics is bread-and-butter ML research work.
This challenge sharpens
- llm-evaluation
- capability-evaluation
- research-writing
Applied AI Scientist
Translating evaluations into policy-relevant observations is the applied-AI bridge into policy and governance teams.
This challenge sharpens
- llm-evaluation
- policy-communication
- research-writing