Job
Description
Area(s) of responsibility Coding and Development: Write clean, using autogen and crew.ai frameworks efficient, and maintainable code for GenAI applications using Python and open-source frameworks. Fine-Tuning Models: Fine-tune LLMs and SLMs using techniques like PEFT, LoRA, and QLoRA for specific use cases. Open-Source Frameworks: Work with frameworks like Hugging Face, LangChain, LlamaIndex, and others to build GenAI solutions. Cloud Tools Integration: Use cloud platforms (Azure, GCP, AWS) to deploy and manage GenAI models and applications. Prototyping: Quickly prototype and demonstrate GenAI applications to showcase capabilities and gather feedback. Data Preprocessing: Build and maintain data preprocessing pipelines for training and fine-tuning models. API Integration: Integrate REST, SOAP, and other APIs for data ingestion, processing, and output delivery. Model Evaluation: Evaluate model performance using metrics and benchmarks, and iterate to improve results. Document Intelligence: Develop solutions for OCR and document intelligence using open-source and cloud-based tools. Front-End Development: Collaborate with front-end developers to integrate GenAI capabilities into user-friendly interfaces using tools like Streamlit or React. Version Control: Use Git and other version control systems to manage code and collaborate with team members. Technical Documentation: Create clear and concise documentation for code, models, and processes. Collaboration: Work closely with data scientists, engineers, and product managers to deliver high-impact solutions. Learning and Growth: Continuously learn and stay updated with the latest advancements in GenAI, open-source tools, and cloud technologies. Debugging and Optimization: Identify and fix bugs, optimize code, and improve application performance. ________________________________________ Required Skills Python Programming: Strong proficiency in CORE Python OOP for developing GenAI applications. Fine-Tuning Techniques: Hands-on experience with fine-tuning methods like PEFT, LoRA, and QLoRA. Open-Source Frameworks: Expertise in Hugging Face, LangChain, LlamaIndex, and other open-source libraries. Cloud Platforms: Familiarity with Azure, GCP, and AWS for deploying and managing GenAI models. Data Preprocessing: Skills in building and maintaining data preprocessing pipelines. API Integration: Experience with REST, SOAP, and other protocols for API integration. Model Evaluation: Knowledge of metrics and benchmarks for evaluating model performance. Document Intelligence: Proficiency in OCR and document intelligence using open-source and cloud tools. Front-End Tools: Basic knowledge of front-end tools like Streamlit, React, or JavaScript for UI integration. Version Control: Proficiency in Git and version control best practices. Technical Documentation: Ability to create clear and concise technical documentation. Problem-Solving: Strong analytical and problem-solving skills to debug and optimize code. Collaboration: Excellent teamwork and communication skills to work effectively in cross-functional teams. Rapid Prototyping: Ability to quickly prototype and demonstrate GenAI applications. Continuous Learning: A growth mindset with a passion for learning and staying updated with the latest GenAI trends and technologies. Show more Show less
