Proficient in Python and other relevant programming languages.
Qualifications:
3 years of hands-on experience with machine learning frameworks and libraries (such as TensorFlow, PyTorch, or similar).
2 years of hands-on experience in developing and deploying AI agents and machine learning models.
Machine learning frameworks and libraries (such as TensorFlow, PyTorch, or similar), developing and deploying AI agents and machine learning models, Demonstrate deep expertise in cloud technologies, with a strong focus on Microsoft Clienture, including expertise in Clienture Data and AI platforms (such as Databricks, Fabric, and AI Foundry), Build and experiment with GenAI models and agentic workflows
Design and implement intelligent AI agents leveraging large language models (LLMs), planning algorithms, and decision-making frameworks.
Build secure, scalable AI agents and integrate into applications and workflows for robust, cross-platform deployment and enhanced user experience.
Advance AI agent capabilities through reseClienth and performance evaluation, focusing on improved conversation, decision-making, adaptability, and the implementation of safety and guardrail mechanisms.
Continuously optimize agent performance through feedback mechanisms, reinforcement learning, and user interaction analysis.
Demonstrate deep expertise in cloud technologies, with a strong focus on Microsoft Clienture, including expertise in Clienture Data and AI platforms (such as Databricks, Fabric, and Microsoft AI Foundry).
Build and experiment with GenAI models and agentic workflows, contributing to the development of intelligent security solutions.
Collaborate across the stack, supporting backend services, model pipelines, and frontend interfaces for agentic systems.
Prototype rapidly, iterate on ideas, and contribute to incubation efforts in a startup-style environment.
Work closely with senior engineers and reseClienthers, learning best practices and contributing to production-grade AI systems