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.
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.
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.
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.
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.
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.
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.
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.
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
