Sr. Data/ML Engineer (Machine Learning)

Location: McLean, VA, USA

Salary: $170,000–$190,000 per year

Company

hirify.global delivers digital services, advanced analytics, artificial intelligence and machine learning, cybersecurity, and other technology solutions to U.S. government agencies.

What you will do

• Develop high-performance data-processing and analytical workflows in Python.
• Prepare, transform, analyze, and validate data using Polars, NumPy, and related Python technologies.
• Perform feature engineering and develop, train, evaluate, and refine predictive machine learning models.
• Build predictive ML capabilities with Scikit-Learn, LightGBM, XGBoost, and related technologies.
• Monitor model performance and identify model or data drift while supporting optimization and calibration.
• Integrate production-ready analytical capabilities and predictive models into the Army Vantage environment and collaborate on end-to-end mission solutions.

Requirements

• 10+ years of data engineering experience, including designing dimensional models for analytical and reporting environments.
• Senior-level data engineering experience with strong Python proficiency.
• Hands-on experience with Polars and NumPy.
• Experience developing predictive machine learning solutions with Scikit-Learn, LightGBM, and XGBoost.
• BS degree in computer science, information technology, engineering, data analytics, or a related technical discipline, or equivalent experience.
• Active Secret security clearance required.

Nice to have

• Experience with Palantir Foundry or Army Vantage.
• Experience operationalizing predictive models in enterprise environments.
• Experience with large or complex government data environments.
• Previous Army, DoD, or federal mission-system experience.

Culture & Benefits

• Medical, dental, vision, life, short-term disability, and long-term disability insurance.
• 11 federal holidays and paid time off.
• 401(k) with company matching.
• Flexible Spending Accounts for commuter, medical, and dependent care expenses.
• Tuition assistance and charitable contribution matching.
• Eligibility for performance-based incentives.