Woongjin, Inc
GEN AI Software Engineer
Woongjin, Inc, Ridgefield Park, New Jersey, us, 07660
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.
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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.
#J-18808-Ljbffr