Data Scientist - AI Safety
Recruiter Fit Breakdown & Candid Summary
This role is for a hands-on data scientist who thrives in high-velocity environments and enjoys bridging the gap between policy, research, and production engineering.
The ideal candidate is comfortable with the 'messy' side of data—collection, labelling, and quality control—rather than just model architecture.
This is not a pure research role; it requires building scalable infrastructure and managing external contributor networks.
Candidates who prefer rigid hierarchies or strictly defined, narrow scopes will likely struggle in this autonomous, impact-driven culture.
Role Responsibilities
- 1Manage the end-to-end lifecycle of safety datasets, including collection, cleaning, labelling, and versioning.
- 2Translate complex safety policies into actionable labelling and evaluation criteria.
- 3Design and oversee external contributor networks to ensure high-quality data labelling.
- 4Build and maintain evaluation workflows to monitor model performance in production environments.
- 5Develop Python and SQL pipelines to automate and scale data processing tasks.
Skills Matrix
Must-Have Skills
Nice-to-Have Skills
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Grounded Observations to Note
Ambiguous Title/Structure
"We don’t have job titles. Instead, it’s about the impact you have."
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