AI Engineer

Role Overview

Cloud Deployment:

AI Agent Development:

Data Analytics:

Data Visualization:

Model Optimization:

Leadership:

Self-Driven Execution:

Continuous Learning:

Education:

Programming:

Data Analytics:

Data Visualization:

Azure Cloud Expertise:

GenAI Methodologies:

Deployment:

LLMOps:

Strategic Thinking:

Problem-Solving:

Collaboration:

- Experience deploying GenAI models in production environments, preferably on Azure Familiarity with multi-agent systems, reinforcement learning, or distributed training (e.g., DeepSpeek). - Knowledge of DevOps practices, including Git, CI/CD, and infrastructure-as-code. Advanced data analytics techniques (e.g., time-series analysis, A/B testing) for GenAI applications. - Experience with interactive visualization frameworks (e.g., Dash, Streamlit) for real-time dashboards. - Contributions to GenAI or data analytics open-source projects or publications in NLP, generative modeling, or data scien