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# Machine Learning Engineer, Government (IL5)

- **Company:** UARE, LLC
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $200,000.0 - $260,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Audit Trail, Microsoft Azure, OpenAI, Azure Machine Learning, Search Technologies, Enterprise Search, Retrieval-Augmented Generation, Large Language Models, Data Lineage, Azure AI
- **Published:** October 22, 2026
- **Apply:** https://startup.jobs/senior-machine-learning-engineer-government-il5-uareai-10523243

## About the Role

* U.S. citizenship is required. This role supports U.S. government contracts that require it.
 * Hands-on experience deploying ML or LLM systems in a DoD IL5 environment (Azure Government preferred).
 * 7+ years in ML or applied AI, owning models that serve real traffic.
 * Deep experience with Azure OpenAI or similar hosted models, RAG, vector search (such as Azure AI Search), and evals.
 * Comfortable in disconnected or tightly restricted environments where you cannot pip install your way out of a problem.
 * Able to pass a U.S. government background investigation. An active clearance is a plus.

## Description

You will make the HLM run on Azure OpenAI inside a Department of Defense/War Impact Level 5 (IL5) boundary, and prove it performs as well there as it does commercially., * Serve the models. Stand up Azure OpenAI and Azure AI Speech in Azure Government, and tune them for quality, latency, and cost.

 * Port the pipelines. Move our RAG and HLM pipelines onto Azure Government services, with nothing leaving the boundary.
 * Prove it works. Build evals for accuracy, grounding, and refusals, and report results to the customer.
 * Own provenance. Model versions, prompts, approved images, and data lineage, documented for the ATO.
 * Bring voice. Run Voice Capture on Azure AI Speech inside IL5.
 * Secure retrieval. Build access control and audit logging with our full stack engineer., * Fine-tuning models on Azure OpenAI or Azure Machine Learning.
 * Iron Bank / Platform One container pipelines.