
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, we’re 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 NPR's 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 organization's 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 NPR's 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 $160,000 - 186,000 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 NPR’s 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 Pay Range
$160,000 - $186,000 USD
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.
If you are a person with a disability needing assistance with the application process, please reach out to employeerelations@npr.org.
You may read NPR’s privacy policy to learn about how NPR may handle information you submit with any application.
Want more NPR? Explore the stories behind the stories on our NPR Extra blog. Get social with NPR Extra on Facebook and Instagram. Find more career opportunities at NPR.org/careers.
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