Key Responsibilities

• Develop and implement production-level Generative AI models within an agentic architecture.
• Utilize local LLMs, OpenAI fine-tuning, and RAG techniques.
• Design and optimize prompts for AI models to enhance performance and user interaction.
• Work with embeddings to improve the accuracy and relevance of AI models.
• Apply data science techniques to extract, cluster, and analyze data to drive AI model improvements.
• Collaborate with cross-functional teams to understand business requirements and translate them into AI solutions.
• Continuously monitor and improve AI models to ensure high performance and accuracy.
• Conduct research and stay up-to-date with the latest advancements in AI and data science.
• Create and maintain comprehensive documentation for AI models and data science processes.

Requirements

• Bachelor's or Master’s degree in Computer Science, Data Science, or a related field.
• Proven experience in developing and deploying Generative AI models in a production environment.
• Strong proficiency in data clustering, data mining, and feature extraction techniques.
• Experience with local LLMs, OpenAI fine-tuning, and Retrieval-Augmented Generation (RAG).
• Proficiency in prompt engineering and working with embeddings.
• Proficiency in programming languages such as Python and C#.
• Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch).
• Strong analytical and problem-solving skills. Excellent communication and teamwork abilities.

Preferred Qualifications:

• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with MLOps practices and tools.
• Knowledge of natural language processing (NLP) techniques and applications.
• Prior experience in a startup or fast-paced tech environment.