AI Model Developer- LLM,RAG - [REMOTE]

Job Title: AI Model Developer

Location: [Remote]

Job Summary:

We are looking for a skilled and innovative AI Model Developer to join our team. The ideal candidate will have hands-on experience with Large Language Models (LLMs), particularly OpenAI and Azure OpenAI, to develop advanced AI solutions. This role involves building, fine-tuning, and deploying AI models that improve performance and user experience.
Key Responsibilities:
• Develop and implement AI models using OpenAI's ChatGPT API or similar LLMs, with a focus on prompt engineering and fine-tuning.
• Leverage retrieval-augmented generation (RAG) techniques for enhanced performance and retrieval capabilities.
• Write Python scripts for data processing, model deployment, and API integration.
• Integrate AI solutions with RESTful APIs and third-party services (e.g., OpenAI).
• Manage structured and unstructured data using SQL and MongoDB.
• Use Azure Databricks for data processing and model training.
• Implement embedding models for efficient vector storage and retrieval.
• Work with distributed data systems such as Databricks and Apache Spark.
• Troubleshoot AI model issues and debug system integrations.
• Conduct clustering, embedding creation, and evaluation for various data types.
• Apply model alignment and bias mitigation strategies.
• Document processes, changes, and system designs for traceability.
• Evaluate embeddings, retrievers, and generation models using tools like LangSmith and MLFlow.

Required Qualifications:
• Experience with OpenAI's ChatGPT API or similar LLMs, including Azure OpenAI for generation and embeddings.
• Familiarity with fine-tuning LLMs and prompt engineering, especially within Azure OpenAI.
• Proficiency in Python for scripting, data processing, and integration tasks.
• Experience working with APIs (OpenAI, RESTful APIs).
• Strong SQL skills and experience with MongoDB, including vector storage/indexing.
• Experience with vector databases such as Pinecone and FAISS.
• Knowledge of databases like Redis, SQL Server, and MongoDB.
• Experience with embedding models for vector data retrieval.
• Solid debugging and integration troubleshooting skills.
• Strong problem-solving and analytical thinking.
• Excellent documentation practices for tracking changes and system designs.
• Familiarity with LangChain and LangGraph frameworks.
• Hands-on experience with Pinecone for vector storage and retrieval.

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