Description
Key Skills: Python, TensorFlow, PyTorch, Machine Learning, Deep Learning, NLP, Generative AI, GANs, Azure OpenAI, AWS
Good to Have Skills: Keras, VAEs, reinforcement learning, Google Vertex Gen AI, BERT, Transformers, PaLM, Bard, Autogen, CrewAI, MCP Server, cloud computing platforms like Google Cloud and Azure, containerization, orchestration of AI models, hyperparameter tuning, optimization techniques.
Roles & Responsibilities:
- Design, develop, and implement cutting-edge generative AI models using state-of-the-art techniques such as General Adversarial Networks, variational autoencoders, and reinforcement learning.
- Collaborate with cross-functional teams to define project goals, research requirements, and develop innovative solutions for AI applications.
- Optimize model performance through experimentation, hyperparameter tuning, and advanced optimization techniques to achieve better results.
- Stay up-to-date on the latest advancements in generative AI, deep learning, and related fields, incorporating new techniques into workflows.
- Develop and maintain clear and concise documentation of generative AI models, processes, and results for team reference.
- Communicate complex concepts and results to both technical and non-technical stakeholders in an understandable manner.
- Provide support and guidance to other team members, contributing to a positive, collaborative working environment.
- Lead the development and deployment leveraging large language models, MCP Server and agentic frameworks such as MAF, Autogen or CrewAI.
- Oversee cloud deployments, containerization, and orchestration of AI models to ensure scalability and reliability in production environments.
Experience Required: 3-6 years of hands-on experience with Python packages like TensorFlow, PyTorch, or Keras, along with demonstrated experience in generative AI techniques.
Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field