Generative AI Engineer - Deep Learning

Role Overview: As a Generative AI Developer at our company, you will be responsible for designing and optimizing Transformer-based models for various generative tasks such as text summarization, Q&A, content creation, and code generation. Your role will involve implementing deep learning techniques, building contrastive learning frameworks, developing information retrieval systems, and collaborating with data scientists and product teams to deliver user-focused GenAI solutions. Key Responsibilities: - Design, develop, and optimize Transformer-based models (e.g., BERT, GPT, T5). - Implement deep learning techniques like batch normalization, dropout, and attention mechanisms. - Build and train contrastive learning frameworks for representation learning. - Develop scalable information retrieval systems using technologies like FAISS. - Optimize model performance for inference using quantization, distillation, and hardware-aware tuning. - Collaborate with data scientists and product teams to define and deliver user-focused GenAI solutions. - Stay updated with state-of-the-art research in generative AI and incorporate best practices into development. Qualifications Required: - Strong hands-on experience with Transformer architectures using frameworks like Hugging Face Transformers, PyTorch, or TensorFlow. - Deep understanding of deep learning fundamentals including backpropagation, batch/layer normalization, and regularization. - Practical experience with contrastive learning paradigms and self-supervised learning strategies. - Solid grasp of information retrieval systems, vector databases, embedding generation, and semantic search methodologies. - Proficiency in Python and ML frameworks like PyTorch, TensorFlow, JAX. - Experience with end-to-end model lifecycle, handling large datasets, and distributed training. - Knowledge of MLOps tools and cloud platforms. (Additional details of the company were not included in the provided job description),