AI/ML Engineer

TechDigital Group; Minneapolis (MN); On-site; USD 110,000 - 170,000; Full time

Job summary

A leading technology firm is seeking an experienced AI Developer proficient in Python and machine learning frameworks like TensorFlow and PyTorch. The role involves designing intelligent AI agents, optimizing performance through feedback analysis, and leveraging cloud technologies with a strong focus on Microsoft Azure. Candidates should have hands-on experience with AI agents and demonstrate expertise in developing GenAI models. This position offers opportunities for collaboration across stacks and integration in a production-grade environment.

Qualifications

• 3 years of hands-on experience with machine learning frameworks.
• 2 years of experience in developing and deploying AI agents and models.
• Expertise in Azure Data and AI platforms.
• Strong Azure cloud expertise, including Azure Data and AI platforms (Databricks, Fabric, AI Foundry).
• Experience building GenAI models and agentic workflows.
• Design and implement intelligent AI agents using LLMs, planning algorithms, and decision-making frameworks.
• Build secure, scalable AI agents integrated into applications and workflows.
• Advance AI agent capabilities via research and performance evaluation.
• Improve agent performance with reinforcement learning and user interaction analysis.
• Collaborate across backend, model pipelines, and frontend for agentic systems.
• Prototype rapidly in a startup-style environment.
• Work closely with senior engineers and researchers.

Responsibilities

• Design and implement intelligent AI agents leveraging LLMs.
• Optimize agent performance through feedback and user interaction.
• Collaborate across the stack for agentic systems.

Skills

Proficient in Python

Machine learning frameworks (TensorFlow, PyTorch)

Cloud technologies expertise (Microsoft Azure)

GenAI models and agentic workflows

Reinforcement learning

Model deployment

Azure

Azure Databricks

Fabric

AI Foundry

GenAI

LLMs

Planning algorithms

Decision-making

Security

Full-stack collaboration

Rapid prototyping

Mentorship

Tools

Databricks

Fabric

Azure AI Foundry

Job description

Must Have

• Proficient in Python and other relevant programming languages.
• 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 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.