Description

Key Responsibilities:
Design and develop advanced Generative AI models for tasks such as content creation, text generation, image generation, and more.
Experience with transformer models, VAEs, GANs, and other generative architectures for different AI-driven projects.
Collaborate with cross-functional teams to integrate Generative AI models into various applications, ensuring alignment with business needs.
Work with large datasets, applying techniques such as data cleaning, feature engineering, and data augmentation.
Implement and optimize deep learning models on GPU and cloud infrastructures for large-scale training and inference.
Stay up-to-date with the latest trends and research in Generative AI and Machine Learning.
Evaluate model performance through rigorous testing, model validation, and fine-tuning.
Requirements:
Strong programming skills in Python and proficiency with ML frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers.
Proven expertise in building and deploying Generative AI models (e.g., GPT, BERT, DALL-E, Stable Diffusion).
Deep understanding of Natural Language Processing (NLP) and working experience with transformers, embeddings, and language models.
Solid experience with Deep Learning techniques, including CNNs, RNNs, and attention mechanisms.
Practical experience with data preprocessing, feature engineering, and handling large-scale datasets.
Familiarity with Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and other generative models.
Demonstrated ability to experiment with different model architectures and optimize for performance.

Education

Bachelor's degree in Computer Science