GENAI with Python Experts

As an ideal candidate, you should have a strong grasp of the Software Development Life Cycle (SDLC), Python Scripting, and Artificial Intelligence (AI) packages. Your conceptual knowledge should extend to General Artificial Intelligence (GenAI) techniques, including Prompt engineering such as Template, Curation, and modification. You should be well-versed in various foundation models related to text, image, video, and other data. Experience in training and integrating Deep Neural Network (DNN) modules, Convolutional Neural Network (CNN), and Transformer/Recurrent Neural Network (RNN) is essential for this role. Additionally, you should possess GenAI knowledge concerning Large Language Models (LLM) and Multimodal Models like Stable diffusion, Autoregression, and Diffusion Transformer for utilizing World Foundation models and peripheral development. Your expertise should also include fine-tuning (Transfer learning) techniques for Multimodal Foundation models, as well as managing Multi-modal Data pipelines involving tasks like cleaning, augmentation, and creating embeddings. You should be familiar with Data pruning/Curation and labeling in the context of AI training and validation. Furthermore, a good understanding of the Autonomous Driving (AD) domain is required, encompassing knowledge of domain stack components, features, sensor configuration, and the format and types of annotations necessary for various components in the stack for development and testing. Your comprehensive skill set in these areas will be crucial for excelling in this position.,