LLM Engineer - Artificial Intelligence Models (3-8 yrs)

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 experience.

Requirements :

- 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 environment.

Requirements :

- 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.