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AI/ML Engineer
Job in
Minneapolis, Hennepin County, Minnesota, 55400, USA
Listed on 2026-02-16
Listing for:
TechDigital Group
Full Time
position Listed on 2026-02-16
Job specializations:
-
Software Development
AI Engineer, Machine Learning/ ML Engineer
Job Description & How to Apply Below
Must Have
- Proficient in Python and other relevant programming languages.
- 3 years of hands-on experience with machine learning frameworks and libraries (such as Tensor Flow, 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 Tensor Flow, PyTorch, or similar), developing and deploying AI agents and machine learning models, Demonstrate deep expertise in cloud technologies, with a strong focus on Microsoft Azure, including expertise in Azure 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 research 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 Azure, including expertise in Azure 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 researchers, learning best practices and contributing to production-grade AI systems.
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