Python Developer - RAG/LLM Model

Job Description

• Design, develop, and maintain backend services using Flask and Django for integrating and deploying RAG-based LLM models.
• Develop RESTful APIs and data pipelines to interact with AI models and integrate them into client-facing applications.
• Build and maintain database models, manage large data sources, and optimize API endpoints for performance.
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Model Integration And Deployment

• Implement and integrate RAG-based LLM models into production environments using Flask and Django frameworks.
• Work closely with AI and data science teams to ensure proper data flow and retrieval between the model and backend systems.
• Optimize model performance for inference efficiency, memory management, and response time.
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Model Optimization And Fine-Tuning

• Fine-tune and optimize LLMs to meet specific business use cases, such as content generation, summarization, and question answering.
• Collaborate with machine learning engineers to improve accuracy, reduce inference times, and scale model usage.
• Monitor and debug model performance and address any issues related to latency or correctness in the model's output.
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Data Management & Analysis

• Handle large datasets and develop data pipelines to provide inputs for training and testing models.
• Ensure proper preprocessing of input data to enhance model performance.
• Write and optimize SQL/NoSQL queries for data extraction, transformation, and storage related to the models.
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Collaboration & Continuous Improvement

• Collaborate with cross-functional teams, including product managers, AI researchers, and front-end developers, to design solutions that meet business goals.
• Write unit and integration tests to ensure the quality of backend components.
• Follow Agile practices for development, including participating in sprint planning, stand-ups, and code reviews.
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Model Monitoring And Maintenance

• Implement monitoring systems to ensure model performance, and address any degradation or anomalies.
• Continuously discover and implement new techniques to improve the efficiency and reliability of the deployed models.
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Required Skills And Qualifications

• 3+ years of experience in Python development with expertise in Flask and Django.
• Strong understanding of AI/ML concepts and experience working with Retriever-Augmented Generation (RAG) models and LLMs (e., GPT, BERT, T5).
• Experience with model deployment and integration of AI models into backend applications.
• Proficiency in Python, including working with libraries such as TensorFlow, PyTorch, Hugging Face Transformers, and spaCy.
• Experience with developing RESTful APIs using Flask or Django REST Framework (DRF).
• SQL/NoSQL Database experience for managing and retrieving large datasets.
• Version control using Git for collaboration.
• Familiarity with deploying applications to cloud platforms (AWS, GCP, Azure).
• Strong problem-solving skills and ability to troubleshoot complex production issues.
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Preferred Skills

• Knowledge of CI/CD pipelines for deploying Python applications.
• Familiarity with Docker and Kubernetes for containerization and orchestration of model deployments.
• Experience with Natural Language Processing (NLP) and data preprocessing techniques.
• Knowledge of distributed computing for scaling AI models.
• Familiarity with tools like FastAPI for faster API development and deployment.
• Knowledge of AI performance monitoring and optimization techniques for large models in production.
• Exposure to marketing analytics, sentiment analysis, or content generation with LLMs.
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Educational Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, or related field.
• Master's degree in a relevant field is a plus