Support an MT&E team by designing, evaluating, and operationalizing AI/ML capabilities for mission-driven analytical objectives.
Responsibilities
- Design, develop, and evaluate machine learning models and algorithms
- Perform modeling, testing, and evaluation across 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
Requirements
- Hands-on experience developing and evaluating machine learning models
- Proficiency in Python and common ML frameworks (examples: TensorFlow, PyTorch, scikit-learn)
- Experience with model testing, validation, and performance assessment
- Strong analytical and problem-solving skills applied to data-driven tasks
Technologies
- Python
- TensorFlow
- PyTorch
- scikit-learn
Required Qualifications
- Active TS/SCI clearance required
- Benz Technology is unable to sponsor security clearances
- U.S. citizenship required
Desired Qualifications
- Experience in a government or IC modeling and evaluation environment
- Familiarity with ML pipeline orchestration and experiment tracking tools
- Experience in applied ML areas such as NLP or computer vision
- Background in statistical analysis or data science
Work Arrangement and Pay
- Location: Fort Meade, MD (hybrid)
- Telework: Up to 16 hours/week after full acclimation and completion of telework training, subject to mission needs and leadership discretion
- Salary: $145,000–$195,000 (annual)
Benefits
- 15% employer 401(k), vested day one, no match required
- 28 paid days off per year
- $7,500 annual tuition reimbursement
- $2,500 training and development budget
- 28 years in business; engineers stay through recompetes
This role supports a Modeling, Test & Evaluation (MT&E) team focused on AI/ML development and analysis. There are two open positions on the same team.