LLM Engineer - Artificial Intelligence Models

Key Responsibilities : - Collaborate with the design and product teams to craft and iterate on engaging conversational experiences for our users. - Develop AI-powered conversational systems that feel natural and deliver high user satisfaction. - Fine-tune and adapt pre-trained large language models (LLMs) to the specific needs of the product and user experience. - Leverage custom datasets, including user interaction data, to enhance model performance and ensure personalized, context-aware responses. - Implement and experiment with various Retrieval-Augmented Generation (RAG) strategies to enhance the AIs capabilities in providing real-time, accurate information. - Use structured and unstructured data to improve the AI's ability to deliver highly relevant and personalized conversational outputs. - Take full ownership of the development process, from conceptualization through deployment, ensuring high-quality, scalable, and reliable AI features. - Work independently to solve complex challenges, while aligning with broader product goals and priorities. - Work closely with cross-functional teams, including data scientists, engineers, and designers, to ensure a seamless integration of AI capabilities into the overall product. - Provide regular updates to the team on progress, challenges, and opportunities. - Assist in setting up the workflows, systems, and tools for building, testing, and deploying conversational AI models in a startup environment. - Contribute to developing infrastructure that allows for efficient experimentation, model training, and deployment. - Stay up to date with the latest trends and advancements in conversational AI, LLMs, and RAG techniques. - Identify and explore new technologies and methodologies to continuously improve the user : - Proven experience in building and deploying conversational bots or AI-powered chat applications. - Solid experience in fine-tuning models for specific use cases, including working with large language models (LLMs) such as GPT, BERT, T5, etc. - Expertise in using Retrieval-Augmented Generation (RAG) techniques to enhance the performance of conversational AI systems. - Familiarity with AI model deployment frameworks and tools, such as TensorFlow, PyTorch, Hugging Face, or similar. - Strong proficiency in Python (for data science, machine learning, and model fine-tuning). - Experience working with Natural Language Processing (NLP) techniques and tools. - Hands-on experience in managing and processing large datasets, including text, structured data, and unstructured content. - Knowledge of cloud platforms (e.g., AWS, GCP, or Azure) and containerization (e.g., Docker, Kubernetes) for deploying AI models at scale. - Ability to translate business and product requirements into actionable technical solutions that improve the user experience. - Experience working in an agile development environment, collaborating with product managers, designers, and engineers. - Strong problem-solving skills and ability to innovate in a fast-paced, startup : - 3-6 years of experience. - Experience working with LLMs and Generative AI. - Experience building conversational bots. - Experience fine-tuning models. - Experience using RAG base approaches. - Understanding financial concepts and investing would be a big plus but not required. (ref:hirist.tech)

Location: in, IN

Posted Date: 11/21/2024