Key Responsibilities :

- Design and develop generative AI models using state-of-the-art techniques like GANs, VAEs, and transformers to address specific client needs.

- Implement and deploy generative AI models on cloud platforms such as AWS and Azure to ensure scalability and reliability.

- Fine-tune pre-trained language models for specific tasks, such as text generation, summarization, and translation, to enhance performance.

- Collaborate with data scientists to preprocess and prepare data for training generative AI models, ensuring data quality and integrity.

- Evaluate the performance of generative AI models using appropriate metrics and techniques to identify areas for improvement.

- Stay up-to-date with the latest advancements in generative AI and related fields to identify opportunities for innovation.

- Communicate technical findings and recommendations to stakeholders in a clear and concise manner to facilitate informed decision-making.

Required Skillset :

- Demonstrated ability to develop and deploy machine learning models using Python and relevant libraries such as TensorFlow and PyTorch.

- Strong understanding of deep learning concepts and architectures, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs).

- Proven experience in natural language processing (NLP) techniques, including text classification, sentiment analysis, and named entity recognition.

- Practical experience with cloud computing platforms such as AWS or Azure, including deploying and managing AI models in the cloud.

- Ability to effectively communicate technical concepts to both technical and non-technical audiences.

- Solid understanding of data modeling and data visualization techniques.

- Bachelor's or Master's degree in Computer Science, Data Science, or a related field.