Senior GenAI Safety & Trust Engineer

Google LLC

Kirkland (WA)

Sur place

USD 159 000 - 230 000

Plein temps

Il y a 2 heures
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Avantages offerts par ce poste

Health insurance
Dental insurance
Vision insurance
Life insurance
Disability insurance
401(k) with company match

Résumé du poste

Google LLC is seeking a Senior Engineering Analyst/Tech Lead within Trust and Safety SAGE to lead the architecture and scaling of automated safety evaluation and enforcement platforms for next-generation generative AI products.

You will own the transition to high-throughput autoraters, enabling real-time launch decisions and continuous offline testing while collaborating with cross-functional teams to ensure safe and responsible AI deployments.

Qualifications

  • Minimum 5 years of experience in data analysis, identifying trends and drawing insights from data.
  • 5 years in the anti-abuse domain, with signal analysis, model development, data analysis, and cybersecurity.
  • Experience programming in SQL, Python, or Golang.

Responsabilités

  • Establish metrics and benchmarks for Generative-AI issues; develop data sets and evals for engineers.
  • Drive project delivery, manage interdependent projects of moderate to high complexity.
  • Improve tools via data analysis and stakeholder presentations; automate workflows.
  • Design, develop, and scale LLM-as-a-judge autoraters and automated evaluation systems for real-time decisions.
  • Collaborate with Product, Search Core, and GDM engineering teams on roadmaps and risk registers.

Connaissances

Data analysis
Anti-abuse domain
Programming (SQL, Python, Golang)

Formation

Bachelor's degree or equivalent practical experience

Description du poste

Google LLC is seeking a Senior Engineering Analyst/Tech Lead within Trust and Safety SAGE to lead the architecture and scaling of automated safety evaluation and enforcement platforms for next-generation generative AI products.

You will own the transition to high-throughput autoraters, enabling real-time launch decisions and continuous offline testing while collaborating with cross-functional teams to ensure safe and responsible AI deployments.

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