Senior AI Engineer, AI Labs

OVERVIEW

A thriving mission-driven multimedia organization NPR produces award-winning news information and music programming in partnership with hundreds of independent public radio stations across the nation. The NPR audience values information creativity curiosity and social responsibility and our employees do too. We are innovators and leaders in diverse fields from journalism and digital media to IT and development. Every day our employees and member stations touch the lives of millions worldwide.

Across our organization were building a workplace where collaboration is essential diverse voices are heard and inclusion is the key to our success. We are committed to doing the right thing in our journalism and in every role at NPR.This means that integrity adherence to our ethical standards and compliance with legal obligations are fundamental responsibilities for every employee at NPR.

Intro to Position

The Senior AI Engineer AI Labs is a foundational role in building NPRs first Generative AI (GAI)-focused product development team. Reporting to the VP of AI Labs this engineer will be responsible for the technical development and implementation of generative AI solutions. The core mission is to engineer systems that leverage GAI to enhance the quality and actionability of our content metadata thereby directly supporting the organizations goals of improving content personalization and increasing editorial efficiency. This role involves hands-on work in integrating AI products into core NPR systems ensuring solutions are scalable align with ethical guidelines and are built upon industry best practices. This is a critical opportunity to shape NPRs technical AI adoption and build a new innovative function.

Responsibilities

• Engineering & Implementation: Design develop and deploy scalable Generative AI (GAI) solutions focusing on enhancing content metadata quality and actionability to meet organizational objectives.
• Architecture & Technical Best Practices: Establish and champion technical best practices for Generative AI systems including MLOps RAG architectures prompt engineering and model evaluation ensuring high-quality maintainable code.
• Cross-functional Development: Collaborate closely with Product Managers data scientists software and infrastructure engineers and relevant subject matter experts to translate product requirements and roadmaps into robust production-ready AI systems.
• System Optimization & Performance: Implement data-driven methods A/B testing and performance monitoring to optimize the efficiency scalability and impact of AI models and pipelines.
• Technical Communication: Clearly articulate technical architectures development progress and engineering challenges to product and non-technical stakeholders.
• Responsible AI: Integrate ethical AI principles and compliance standards directly into the design and implementation of all AI products in alignment with company policies.
• Technology Scouting: Research and evaluate emerging AI technologies frameworks and industry trends to drive continuous technical innovation within the AI Labs.

The above duties and responsibilities are not an exhaustive list of required responsibilities duties and skills. Other duties may be assigned and this job description is subject to change at any time.

Minimum Qualifications

• 5 years of professional experience in software development data science or machine learning engineering with a focus on building and deploying production systems.
• 2 years of hands-on experience working with generative AI machine learning or data products.
• Expert proficiency in Python and experience creating functional prototypes to validate technical feasibility and user flows.
• Demonstrable understanding and experience building products that leverage Large Language Models RAG architectures prompting function calling retrieval vector databases embeddings fine-tuning and model evaluation.
• Familiarity with building and integrating MCP servers and agentic workflows
• Background in creating QA systems for AI processes and development
• Excellent communication skills and the ability to clearly articulate technical architectures and challenges to product and non-technical stakeholders.
• A collaborative and respectful approach to work and an ability to adapt quickly to change.
• A deep commitment to the mission of NPR and to the responsible implementation of Generative AI technologies.

Preferred Qualifications

• Experience designing and building highly scalable production-grade AI/ML pipelines and services.
• Proficiency with cloud platforms particularly AWS and Google Cloud Platform (GCP) and MLOps tools particularly MLFlow and Vertex AI.
• Experience with DevOps practices including CI/CD and enterprise infrastructure-as-code.
• Experience working in media organizations and an understanding of media delivery systems.

Work Location & Requirements

• Hybrid Permitted: This is a hybrid permitted role. Some aspects of this role include duties that are better performed at an NPR facility. The employee will be required to be in the office preferably at the Washington D.C. location at least two to three days a week.

Job Type

• This is a full-time exempt position.

Compensation

Salary Range: The U.S. based anticipated salary range for this opportunity is $160000 - 186000 plus benefits. The range displayed reflects the minimum and maximum salaries NPR expects to provide for new hires for the position across all US locations.

NPR offers access to comprehensive benefits for employees and dependents. Regular full-time employees scheduled to work 30 hours or more per week are eligible to enroll in NPRs benefits options. Benefits include access to health and wellness paid time off and financial well-being. Plan options include medical dental vision life/ accidental death and dismemberment long-term disability short-term disability and voluntary retirement savings to all eligible NPR employees.

Does this sound like you If so we want to hear from you.

NPR is an Equal Opportunity Employer. NPR is committed to being an inclusive workplace that welcomes diverse and unique perspectives all working toward the same goal to create a more informed public. Qualified applicants receive consideration for employment without regard to race color ethnicity national origin ancestry age religion religious belief sex (including pregnancy childbirth and related medical conditions lactation and reproductive health decisions) sexual orientation gender gender identity or expression transgender status gender non-conforming status intersex status sexual stereotypes nationality citizenship status personal appearance marital status family status family responsibilities military status veteran status mental and physical disability medical condition genetic information genetic characteristics of yourself or a family member political views and affiliation unemployment status protective order status status as a victim of domestic violence sexual assault or stalking or any other basis prohibited under applicable law.

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