- Generative AI System Design: Architect and implement advanced generative AI models, focusing on applications such as image and text generation, content creation, and synthetic data generation.
- Model Development and Optimization: Develop, fine-tune, and optimize generative AI models, ensuring they meet performance, scalability, and business objectives.
- AI/ML Integration: Apply solid data science principles to enhance AI/ML models, using statistical analysis and machine learning techniques to improve model accuracy and efficiency.
- Cross-functional Collaboration: Work closely with data engineers, software developers, and product managers to integrate generative AI models into products and services, aligning with business objectives.
- Innovation Leadership: Stay at the forefront of AI/ML and generative AI advancements, driving the adoption of new technologies and best practices within the team.
- Ethical AI Implementation: Ensure that AI models are designed and deployed with ethical considerations, adhering to industry standards and regulatory requirements.
Requirements :
- Experience: AI, Machine Learning, Data Science, or a related field, with 5+ years of experience in AI/ML, particularly with generative AI models.
- Technical Skills: 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 Lang Chain.
- Data Science Expertise: Solid experience in applying data science principles, including statistical analysis, data preprocessing, and machine learning, to enhance AI/ML models.
- Techniques/Approaches: Familiarity with advanced techniques such as Retrieval-Augmented Generation (RAG), fine-tuning, prompt engineering, and zero-shot learning.
- Domain Knowledge: Familiarity with NLP or computer vision related to generative AI applications.