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sql python machine learning spark llmsπ Description
- Design automated adversarial testing for GenAI products.
- Build hybrid evaluation pipelines with LLM judges, classifiers, and rules.
- Develop harm taxonomies aligned with Pinterest's safety threat models.
- Create adaptive loops that learn from attack outcomes to surface vulnerabilities.
- Apply statistical methods to evaluate AI safety, metrics, and coverage.
- Collaborate with ML engineers, Safety, policy, product, and legal teams.
π― Requirements
- 5+ years of data analysis in fast-paced, data-driven environments.
- Hands-on AI safety/adversarial ML, red teaming, or trust & safety.
- Deep familiarity with LLMs and generative AI failure modes (bias, prompts, safety).
- Experience building AI eval frameworks (LLM-as-judge, classifiers, benchmarks).
- Strong Python, SQL/Spark, ML pipelines, and large-scale experimentation.
- Familiarity with AI safety taxonomies (OWASP LLM Top 10, MITRE ATLAS) preferred.
π Benefits
- Equal opportunity employer with an inclusive culture.
- Flexible work arrangements (Pinflex) to help you do your best work.
- Pinterest is committed to inclusion and equal opportunity for all.
- Relocation assistance is not offered for this position.
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