Geopaq Logic Inc
GEN AI Software Engineer
Geopaq Logic Inc, Ridgefield, New Jersey, us, 07657
Job Title: GEN AI Software Engineer
Contract Period: 9/15/2024 - 8/31/2025
Work location: Ridgefield Park, NJ
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) systemsIntegrate and optimize Large Language Models (LLMs) via APIsDevelop efficient information retrieval and extraction systemsBuild and manage databases and vector storesApply Natural Language Processing (NLP) techniquesMonitor performance and continuously improve systemsIntegrate LLM solutions with other third-party tools and in-house applicationsDesign and implement APIs for seamless integration of LLM capabilities
Requirements:
Bachelor's degree or higher in Computer Science, Artificial Intelligence, or related field (Master's preferred)Proficiency in Python programmingDeep understanding of LLMs, RAG systems, and API integrationExperience with NLP and machine learningStrong skills in database and API developmentKnowledge of distributed systems and cloud computingExpertise in integrating AI models with various software solutions
Preferred Qualifications:
Contributions to open-source LLM projectsExperience building AI systems in large-scale production environmentsExperience with vector databases (e.g., Pinecone, Faiss)Proficiency with relevant libraries such as Transformers, Hugging FaceExperience with AWS Bedrock for AI/ML model deployment and managementExperience with microservices architecture (MSA) in cloud environmentsFamiliarity with LLM API providers (e.g., OpenAI, Anthropic, Cohere)
Suggested Tech Stack:
Language: PythonFrameworks: PyTorch or TensorFlow, FastAPI or Flask for API developmentDatabases: PostgreSQL, MySQL, MongoDB,Vector Stores: Pinecone, FaissCloud Platforms: AWS (including Bedrock), Google Cloud, or AzureIntegration Tools: Apache Kafka, RabbitMQ
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Contract Period: 9/15/2024 - 8/31/2025
Work location: Ridgefield Park, NJ
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) systemsIntegrate and optimize Large Language Models (LLMs) via APIsDevelop efficient information retrieval and extraction systemsBuild and manage databases and vector storesApply Natural Language Processing (NLP) techniquesMonitor performance and continuously improve systemsIntegrate LLM solutions with other third-party tools and in-house applicationsDesign and implement APIs for seamless integration of LLM capabilities
Requirements:
Bachelor's degree or higher in Computer Science, Artificial Intelligence, or related field (Master's preferred)Proficiency in Python programmingDeep understanding of LLMs, RAG systems, and API integrationExperience with NLP and machine learningStrong skills in database and API developmentKnowledge of distributed systems and cloud computingExpertise in integrating AI models with various software solutions
Preferred Qualifications:
Contributions to open-source LLM projectsExperience building AI systems in large-scale production environmentsExperience with vector databases (e.g., Pinecone, Faiss)Proficiency with relevant libraries such as Transformers, Hugging FaceExperience with AWS Bedrock for AI/ML model deployment and managementExperience with microservices architecture (MSA) in cloud environmentsFamiliarity with LLM API providers (e.g., OpenAI, Anthropic, Cohere)
Suggested Tech Stack:
Language: PythonFrameworks: PyTorch or TensorFlow, FastAPI or Flask for API developmentDatabases: PostgreSQL, MySQL, MongoDB,Vector Stores: Pinecone, FaissCloud Platforms: AWS (including Bedrock), Google Cloud, or AzureIntegration Tools: Apache Kafka, RabbitMQ
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