Responsibilities :

- Architect and implement advanced generative AI models, focusing on applications such as image and text generation, image and document extraction, RAG, Prompt engineering, and synthetic data generation.

- Advanced Prompt Engineering techniques. Stay at the forefront of AI/ML and generative AI advancements, driving the adoption of new technologies and best practices within the team.

- Develop, fine-tune, and optimize generative AI models, ensuring they meet performance, scalability, and business objectives. Firm grasp on tools to compare outputs of each model and compare against each other.

- Apply solid data science principles to enhance AI/ML models, using statistical analysis and machine learning techniques to improve model accuracy and efficiency.

- Work closely with data engineers, software developers, and product managers to integrate generative AI models into products and services, aligning with business objectives.

- Ensure that AI models are designed and deployed with ethical considerations, adhering to industry standards and regulatory requirements.

Minimum Qualifications / Skills :

- Bachelor's or Master's degree in computer science, AI, Machine Learning, Data Science, or a related field, with 5+ years of experience in AI/ML, particularly with generative AI models.

- Strong expertise in developing and deploying generative AI models.

- Proficiency in Python and experience with AI development libraries such as TensorFlow and PyTorch.

- Experience with Azure OpenAI, Open Source LLMs, and LangChain.

- Solid experience in applying data science principles, including statistical analysis, data preprocessing, and machine learning, to enhance AI/ML models.

Preferred Qualifications/ Skills :

- Familiarity with advanced techniques such as Retrieval-Augmented Generation (RAG), fine-tuning, prompt engineering, and zero-shot learning.

- Familiarity with NLP or computer vision related to generative AI applications.