> Markdown version of [/jobs/ext/4396688-ai-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/4396688-ai-machine-learning-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# AI / Machine Learning Engineer

- **Company:** BENZ TECHNOLOGY, INC.
- **Location:** Fort Meade, MD, United States (Remote available)
- **Salary:** $145,000.0 - $195,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Vision, Iterative and Incremental Development, Python (Programming Language), Machine Learning, Tensorflow, Pytorch, Scikit Learn, Data Analytics, Machine Learning Operations, Data Pipelines
- **Published:** October 13, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=bde9bded4a3ab751

## About the Role

* Hands-on experience developing and evaluating machine learning models
 * Proficiency in Python and common ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
 * Experience with model testing, validation, and performance assessment
 * Strong analytical and problem-solving skills applied to data-driven tasks, * Experience in a government or IC modeling and evaluation environment
 * Familiarity with ML pipeline orchestration and experiment tracking tools
 * Experience with NLP, computer vision, or other applied ML domains
 * Background in statistical analysis or data science

## Description

This role supports a Modeling, Test & Evaluation (MT&E) team focused on AI/ML development and analysis. You will apply machine learning techniques to assess, validate, and improve models in support of mission-driven analytical objectives. This is one of two open positions on the same team., * Design, develop, and evaluate machine learning models and algorithms

 * Conduct modeling, testing, and evaluation of AI/ML systems and pipelines
 * Analyze model performance and recommend improvements based on evaluation results
 * Collaborate with team members to integrate ML solutions into operational workflows
 * Document findings, methodologies, and model performance metrics
 * Support iterative development and testing cycles for AI/ML tools and applications