Generative AI Expert

Key Responsibilities:

• Design Development: Lead the design, development, and optimization of LLM-based chatbots and AI agents, driving innovation in AI-driven applications.
• LangChain Implementation: Implement LangChain to build scalable, efficient, and effective AI-driven applications and services.
• RAG Pipeline Integration: Develop and integrate Retrieval-Augmented Generation (RAG) pipelines to enhance data retrieval and improve the performance of chatbots.
• VectorDB Utilization: Use VectorDB for fast and efficient similarity search, ensuring relevant data retrieval to optimize AI responses.
• AI Inference with Groq: Leverage Groq for AI inference and acceleration, optimizing performance and scalability of AI models and systems.
• LLM Fine-Tuning: Fine-tune and customize large language models (such as GPT-4, LLama, Mistral, or Falcon) to align with business objectives and improve model outputs.
• Cross-Functional Collaboration: Collaborate closely with product managers, data scientists, and engineering teams to integrate AI models into diverse applications and platforms.
• Scalability Performance: Ensure that AI solutions are scalable, secure, and performant under real-world conditions.
• Continuous Learning: Stay up-to-date with the latest advancements in AI, NLP, machine learning, and deep learning, continuously integrating innovative techniques into our AI systems.

Required Skills Qualifications:

• LLM-Based Chatbots: Proven experience in developing and deploying LLM-based chatbots and AI agents.
• LangChain, RAG, and VectorDB: Expertise in LangChain, RAG, and VectorDB technologies for building advanced AI-driven systems.
• Groq Experience: Hands-on experience using Groq for AI inference and acceleration, optimizing AI model performance.
• Programming Proficiency: Strong proficiency in Python and Node.js for AI and machine learning development.
• LLM Fine-Tuning: Experience with fine-tuning LLMs (e.g., GPT-4, LLama, Mistral, Falcon) to meet specific use cases and business needs.
• Machine Learning Expertise: Solid understanding of machine learning, deep learning, and NLP techniques.

Preferred Qualifications:

• API Experience: Experience with APIs from platforms like OpenAI, Hugging Face, and Anthropic.
• Prompt Engineering RLHF: Knowledge of prompt engineering and reinforcement learning from human feedback (RLHF).
• Multimodal AI Solutions: Experience in developing multimodal AI solutions, integrating text, image, video, or speech models.