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# AI/ML Engineer

- **Company:** OnwardPath Technology Solutions LLC
- **Location:** Green Bay, United States (Remote available)
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Information Engineering, Machine Learning, Azure Machine Learning, Search Technologies, Enterprise Software Applications, Large Language Models, Generative AI, Information Technology, Data Management, Machine Learning Operations, Serverless Computing, Databricks
- **Published:** July 31, 2026
- **Apply:** https://www.dice.com/job-detail/8a66b2a9-066e-465c-aa10-7660927ad3ac

## About the Role

* Experience in AI/ML engineering and data science.
 * Strong hands-on experience with Large Language Models (LLMs).
 * Experience developing Generative AI applications using Azure OpenAI Service.
 * Strong experience with Azure Databricks for data engineering, model training, and ML workflows.
 * Expertise in Azure Machine Learning (Azure ML)., * Bachelor''s or Master''s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field.

## Description

We are seeking an experienced AI/ML Engineer with strong expertise in Large Language Models (LLMs), Azure AI Services, Azure Databricks, and Machine Learning. The ideal candidate will design, develop, and deploy enterprise-grade AI solutions using modern GenAI frameworks, scalable data platforms, and cloud-native services on Microsoft Azure., * Design, build, and deploy scalable AI/ML and Generative AI solutions on Microsoft Azure.

 * Develop enterprise applications leveraging LLMs, Azure OpenAI, and RAG architectures.
 * Build and optimize machine learning pipelines using Azure Databricks and Azure ML.
 * Fine-tune and evaluate foundation models for business use cases.
 * Develop prompt engineering strategies to improve LLM performance and accuracy.
 * Integrate vector databases for semantic search and knowledge retrieval.
 * Collaborate with data engineers, architects, and business stakeholders to deliver AI-driven solutions.
 * Monitor, optimize, and maintain AI models in production environments.
 * Ensure security, scalability, and governance of AI applications on Azure.


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