ML / Research Engineer, Safeguards

When to Use

• Define research questions on harm detection, jailbreak resistance, or policy categories
• Curate or audit safety datasets — labeling guidelines, bias checks, version control
• Train or fine-tune classifiers, rankers, or small LLM judges for moderation
• Design benchmarks and eval suites — golden sets, adversarial slices, regression harnesses
• Run ablations — architecture, threshold, data mix, ensemble vs single model
• Analyze metrics — precision/recall, calibration, false positive/negative slices
• Write research memos — methods, results, limitations, production recommendation
• Specify promotion bar for a new safeguard model version

When NOT to Use