• Collect and prepare data for training and evaluating LLMs. This may involve cleaning and processing text data or creating synthetic data.
• Develop and optimize large-scale language models like GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders)
• Work on tasks involving language modeling, text generation, understanding, and contextual comprehension.
• Regularly review and fine-tune OpenAI models to ensure maximum accuracy and relevance for custom datasets.
• Build and deploy AI applications on cloud platforms, particularly AWS.
• Integrate AI models with our company's data to enhance and augment existing applications.

 Strong foundation in machine learning, deep learning, and computer science.

· Expertise in generative AI models and techniques (e.g., GANs, VAEs, Transformers).

· Experience with natural language processing (NLP) and computer vision is a plus.

· Ability to work independently and as part of a team.

· Knowledge of advanced programming like Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. This includes the ability to implement and manipulate complex algorithms fundamental to developing generative AI models.

· Knowledge of Natural language processing (NLP) for text generation projects like text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models.

· Experience in Data management, including data pre-processing, augmentation, and generation of synthetic data. This involves cleaning, labeling, and augmenting data to train and improve AI models.

· Experience in developing and deploying AI models in production environments.

• Knowledge of cloud services (AWS, Azure, GCP) and understanding of containerization technologies like Docker and orchestration tools like Kubernetes for deploying , managing and scaling AI solutions
• Should be able to bring new ideas and innovative solutions to our clients