Lead Generative AI Solutions Engineer

Nationalpublicradioinc; Washington (District of Columbia); Hybrid; USD 187,000 - 208,000; Full time

Benefits offered by this job

Comprehensive health benefits

Paid time off

Retirement savings options

Job summary

Nationalpublicradioinc is seeking a Lead AI Solutions Engineer for its AI Labs team. This foundational role involves designing and implementing generative AI solutions aimed at enhancing content metadata quality to support NPR's goals of improving content personalization.

The ideal candidate will have significant experience in software development and proficiency in Python. The role requires a collaborative approach and a deep commitment to ethical AI practices while working in a hybrid environment from Washington, D.C., at least two days a week.

Qualifications

• 8+ years of experience in software development, data science, or machine learning engineering.
• 2+ years of experience with generative AI, machine learning, or data products.
• Expert proficiency in Python.
• Ability to articulate technical architectures to stakeholders.
• A collaborative approach to work.

Responsibilities

• Design, develop, and deploy scalable Generative AI solutions.
• Establish technical best practices for AI systems.
• Collaborate with teams to create production-ready AI systems.
• Optimize AI models and pipelines through data-driven methods.
• Integrate ethical AI principles into AI products.

Skills

Software development

Data science

Machine learning engineering

Generative AI

Python proficiency

Communication skills

Tools

AWS

Google Cloud Platform

MLOps tools

Job description

Nationalpublicradioinc is seeking a Lead AI Solutions Engineer for its AI Labs team. This foundational role involves designing and implementing generative AI solutions aimed at enhancing content metadata quality to support NPR's goals of improving content personalization.

The ideal candidate will have significant experience in software development and proficiency in Python. The role requires a collaborative approach and a deep commitment to ethical AI practices while working in a hybrid environment from Washington, D.C., at least two days a week.