Company Description
For More Open Positions Visit us at:
http://recruiting.woongjininc.com/
Our Mission
WOONGJIN INC. is a rapidly growing team who provides a range of unique, exceptional, and enhanced services to our clients. We have a strong moral code that includes the service of goodness without expectations of reward. We are motivated by the sense of responsibility and servant leadership.
Job Description
We're seeking a skilled engineer to lead the development of cutting-edge RAG applications using state-of-the-art LLM technologies. The ideal candidate will have a strong background in AI and NLP, with hands-on experience in building and optimizing LLM-based systems. This role requires expertise in integrating LLM solutions via APIs with both third-party tools and in-house applications. Experience with AWS Bedrock is highly valued, and familiarity with microservices architecture in cloud environments is a significant plus.
Primary Responsibilities:
- Design and implement RAG (Retrieval-Augmented Generation) systems
- Integrate and optimize Large Language Models (LLMs) via APIs
- Develop efficient information retrieval and extraction systems
- Build and manage databases and vector stores
- Apply Natural Language Processing (NLP) techniques
- Monitor performance and continuously improve systems
- Integrate LLM solutions with other third-party tools and in-house applications
- Design and implement APIs for seamless integration of LLM capabilities
Salary: 100K-110K a year
Qualifications
Requirements:
- Bachelor's degree or higher in Computer Science, Artificial Intelligence, or related field (Master's preferred)
- Proficiency in Python programming
- Deep understanding of LLMs, RAG systems, and API integration
- Experience with NLP and machine learning
- Strong skills in database and API development
- Knowledge of distributed systems and cloud computing
- Expertise in integrating AI models with various software solutions
Preferred Qualifications:
- Contributions to open-source LLM projects
- Experience building AI systems in large-scale production environments
- Experience with vector databases (e.g., Pinecone, Faiss)
- Proficiency with relevant libraries such as Transformers, Hugging Face
- Experience with AWS Bedrock for AI/ML model deployment and management
- Experience with microservices architecture (MSA) in cloud environments
- Familiarity with LLM API providers (e.g., OpenAI, Anthropic, Cohere)
Additional Information
All your information will be kept confidential according to EEO guidelines.