Overview
Skills
Job Details
| Description for Internal Candidates |
Key Responsibilities:
Model Development: Design and develop algorithms for generative models using deep learning techniques.
Collaboration: Work with cross-functional teams to integrate D solutions into existing systems.
Research: Stay updated on the latest advancements in generative AI technologies and methodologies.
Optimization: Fine-tune models for performance and efficiency.
Troubleshooting: Address and resolve issues related to generative AI models and implementations.
Documentation: Create and maintain comprehensive documentation for AI models and their applications.
Communication: Explain complex technical concepts to non-technical stakeholders.
Required Skills and Qualifications:
6+ years of strong background in machine learning and deep learning algorithms.
Proficiency in programming languages such as Python, with experience in frameworks like TensorFlow and PyTorch.
Familiarity with natural language processing (NLP) techniques and transformer models (e.g., GPT, BERT)
Hands on experience with prompt structures and fine-tune model outputs to align with business needs and user expectations.
Experience with generative AI techniques, including Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs).
Skills in data preprocessing and feature engineering for AI model training.
Strong understanding of neural network architectures and optimization techniques.
Experience in deploying AI models into production environments.
Ability to stay updated with the latest advancements in generative AI research and incorporate them into work.