Director of AI/ML Engineering & Responsible AI

Verizon

Bakersfield (CA)

Hybrid

USD 126,000 - 242,000

Full time

6 days ago
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Benefits offered by this job

Health benefits
401(k) matching
Paid vacation growth with service
Tuition assistance

Job summary

Verizon seeks an experienced leader to serve as the strategic bridge across the enterprise, working daily with VP/SVP-level executives across Legal, InfoSec, and Responsible AI. You will guide AI product owners, direct a team of Principal AI Engineers and Scientists, and ensure compliance with AI safety standards and governance while scaling data science capabilities.

The role emphasizes collaboration, scale, and accountable deployment decisions in a hybrid work environment.

Qualifications

  • Bachelor's degree or four or more years of work experience.
  • Ten or more years of relevant experience required, demonstrated through work, military, or training.
  • Three or more years of managing high-performing engineering/AI teams.
  • Experience in AI Science/Engineering.

Responsibilities

  • Act as the primary strategic bridge across the enterprise, interfacing daily with VP and SVP executives across Legal, InfoSec, and Responsible AI.
  • Partner with AI Platform Engineering leaders to guide AI product owners for compliance.
  • Direct a team of Principal AI Engineers and Scientists.
  • Rely on AI safety standards and compliance frameworks to guide decisions.
  • Utilize dashboards and cloud governance to make go/no-go deployment calls.
  • Ensure data science models scale from pipelines to production.

Skills

AI architecture
LLMOps
Distributed systems
Enterprise risk management

Education

Bachelor's degree
Master's degree (preferred)

Job description

Verizon seeks an experienced leader to serve as the strategic bridge across the enterprise, working daily with VP/SVP-level executives across Legal, InfoSec, and Responsible AI. You will guide AI product owners, direct a team of Principal AI Engineers and Scientists, and ensure compliance with AI safety standards and governance while scaling data science capabilities.

The role emphasizes collaboration, scale, and accountable deployment decisions in a hybrid work environment.

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