NAVER Search US - Applied Scientist (Generative AI & LLMs)

About Naver U.Hub
NAVER U.Hub is the U.S. subsidiary of NAVER, a global internet technology company based in Los Angeles with offices in Seattle and Redwood City. Our teams across Naver Search US, BAND, ThingsBook, and Naver Ventures collaborate to advance AI, social media, and investment initiatives that build smarter and more connected experiences for global users.

Overview
NSU plays a key role in advancing NAVER’s artificial intelligence capabilities. Our team develops cutting-edge technologies that transform the way users interact with digital services. By leveraging natural language understanding, NSU delivers personalized and intuitive experiences that connect seamlessly with each individual. We ensure that NAVER’s technology evolves in real time, adapting to users’ changing needs, whether by refining search results or building smarter tools for the future.

About the Role
We are seeking an Applied Scientist to advance the capabilities of state-of-the-art AI-powered services. In this role, you will contribute to the development of Large Language Model (LLM)-driven systems that power a scalable and intelligent multi-agent ecosystem across diverse domains.
You will play a key role in enabling AI agents to reason, plan, and interact autonomously with external tools and knowledge sources. This position focuses on improving model quality, reliability, and contextual accuracy to deliver high-impact AI solutions in real-world applications.

Key Responsibilities

• Design, develop, and fine-tune Large Language Models (LLMs) and generative AI systems
• Build and optimize multi-agent frameworks that support reasoning, planning, and tool usage
• Design and conduct experiments to evaluate model performance, latency, and output quality
• Improve model reliability by reducing hallucinations and enhancing contextual understanding
• Optimize context utilization and prompt strategies for better model efficiency and accuracy
• Collaborate with cross-functional teams to deploy scalable AI solutions into production
• Stay up to date with the latest advancements in generative AI, NLP, and deep learning

Skills & Qualifications

• 3 to 5 years of professional experience in applied machine learning, NLP, or deep learning.
• A Master’s degree or PhD in Computer Science, Machine Learning, or a closely related field.
• Strong proficiency in Python and modern deep learning frameworks (e.g., PyTorch).
• Demonstrated experience with Generative AI, Transformer architectures, and evaluating model outputs.
• A highly collaborative approach to translating research concepts into tangible product features.

Preferred Qualifications: 

• A PhD or Master’s degree in Computer Science, Machine Learning, or a closely related field.
• Full-time industry experience in applied machine learning or related computer science field.
• Comfortable utilizing AI-powered tools like GitHub Copilot, Cursor, and ChatGPT.

Compensation & Benefits

Salary Range:

• $130,000 - $180,000 per year. Actual compensation may vary based on experience, skills, and location.

Additional Compensation:

• Performance-based bonus

Benefits include:

• Medical, dental, and vision insurance
• 401(k) retirement plan with company match
• Paid time off (vacation, sick leave, and holidays)
• Paid parental leave
• Ancillary Insurance (LTD, STD, AD&D and Life)
• Wellness Program

Other

• Job type: Full-time
• Hybrid (Bellevue, Washington)
• Candidates who pass the initial HR screening will be invited to complete a coding test.
• Please note: To be eligible, applicants must be currently authorized to work in the United States on a full-time basis. Sponsorship for employment visa status is unavailable.

Equal Employment Opportunity

NAVER U.Hub is proud to be an Equal Opportunity Employer, fostering a diverse and inclusive workplace where all individuals are valued and respected. Naver U.Hub and its affiliated companies are committed to providing an Equal Employment Opportunity for all individuals regardless of race, color, religion, gender, age, national origin, marital status, sexual orientation, gender identity, status as a protected veteran, genetic information, status as a qualified individual with a disability, or any other characteristic protected by law.