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# Mid AI/ML Engineer

- **Company:** Ignite, LLC
- **Location:** Washington, DC, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $143,763.0
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, CompTIA Security+, Python (Programming Language), Machine Learning, Performance Tuning, Rust (Programming Language), Scripting, Large Language Models, Prompt Engineering, Kubernetes, Machine Learning Operations, Databricks
- **Published:** July 24, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=ce63dd71338e5cb9

## About the Role

* Deep experience building LLM-based systems and RAG architectures.

 * Strong proficiency in MLOps tools (e.g. MLFlow, Kubeflow, Airflow).

 * Advanced scripting (e.g. Python, JavaScript, Rust).

 * Expertise deploying models on AWS, Azure, or GCP.

 * Ability to work independently with broad responsibilities.

Desired Skills:

 * Experience with scientific datasets or multi-domain research workflows.

 * Familiarity with AWS Bedrock, Databricks, vector databases or comparable technologies.

 * Strong foundation in prompt engineering or AI agents.

 * Experience working with federal clients.

Clearance Requirements:

 * U.S. Citizen - Secret or TS/SCI eligible

Education & Experience:

 * Bachelor's degree in CS, engineering, mathematics, or related field.

 * 3+ years AI/ML professional experience.

 * Intermediate certifications (CCSP, CFR, FITSP-M, GSEC, Security+, SSCP) or advanced certifications (SecurityX / CASP+, GCSA, GSLC, CISSP).

## Description

Ignite Digital Services is hiring an AI/ML Engineer to independently contribute to developing and optimizing advanced AI/ML systems and components in support of a large federal enterprise multi-domain data ecosystem. You will operate with autonomy, apply creative solutions, and influence major technical deliverables, while delivering within a larger team project management environment., * Independently develop and optimize ML models, pipelines, and platform components.

 * Build RAG architectures and high-performing inference systems.

 * Create scalable infrastructure to support training, experimentation, and deployment.

 * Lead integration of AI/ML models into production systems.

 * Conduct advanced troubleshooting and performance tuning.

 * Collaborate with stakeholders to accelerate mission-driven insights.


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