Python Developer AI

Key Responsibilities: 1. Develop and maintain advanced Python applications, emphasizing AI and machine learning techniques. 2. Implement and manage AI-driven projects, e.g. utilizing Pinecone for efficient similarity search and LangChain for sophisticated language processing. 3. Lead the training and utilization of Large Language Models (LLMs) 4. Build and maintain data pipelines and backend systems for AI workflows. 5. Integrate data analytics, employing libraries like Pandas, NumPy, and Scikit-learn to process and analyze large datasets. 6. Design, implement, and optimize data storage solutions tailored for AI applications. 7. Ensure the highest performance and responsiveness of applications focusing on AI-driven data processing and analysis. 8. Lead the integration of AI technologies into existing backend services and databases, emphasizing scalability and efficiency. 9. Maintain code quality, organization, and automatization for AI-related projects. 10. Stay abreast of the latest advancements in AI, machine learning, vector search technologies like Pinecone, and language models like LangChain. 11. Collaboration and Code Review: Work collaboratively in a team environment, participate in code reviews, and share knowledge with team members.Qualifications 1. Bachelor’s/Master’s degree in Computer Science, Engineering, AI, or a related field. 2. Proven expertise in Python development, specifically in AI and data analytics. 3. Solid experience with AI and machine learning libraries and frameworks. 4. Demonstrated experience with Pinecone, LangChain, or similar emerging AI technologies. 5. Strong background in backend development and architecture design. 6. In-depth understanding of databases, both SQL and NoSQL, for AI-driven applications. 7. Familiarity with cloud services (AWS, etc.) and their AI services. 8. Strong understanding of Git and GitFlow. Preferred Skills: 1. Knowledge of frontend technologies (JavaScript, HTML5, CSS) for integrating AI-driven backends. 2. Experience in containerization and orchestration (Docker, Kubernetes). 3. Understanding of CI/CD practices in AI-centric development environments. #J-18808-Ljbffr