Software Engineer-Data Engineering, Machine Learning (ML)
Not Disclosed•Full-TimeOn-site
location_on260, North Columbus Street, Brandon Village, Bluemont, Ballston, Arlington, Arlington County, Virginia, 22203, United States
About the Team
The IT Division supports State and Federal agencies by developing and operating critical information systems for the administration of motor vehicles and driver licenses. Our mission is to ensure system reliability, operational intelligence, and data-driven decision-making across the AAMVA ecosystem.
About the Role
The Machine Learning Data Engineer is a pivotal role designed to bridge the gap between raw data and actionable intelligence. You will be responsible for the full lifecycle of machine learning solutions, from data acquisition and feature engineering to production deployment and ongoing monitoring.
Currently, your work will focus on anomaly detection across high-volume messaging networks, but the scope extends to any ML capability that strengthens system reliability. You will operate outside of a data silo, collaborating with IT, operations, and leadership to translate complex operational problems into robust data solutions. This role requires a professional who can independently manage projects, navigate ambiguity, and communicate technical trade-offs clearly to both technical and non-technical stakeholders.
Hiring Process
Candidates selected for this position will undergo a standard evaluation process including an initial screening, technical assessment of data engineering and ML capabilities, and a final interview with the hiring team to assess cultural fit and communication skills.
Equal Opportunity
AAMVA is an Equal Opportunity Employer/Veterans/Disabled. We are committed to building a diverse workforce and consider qualified applicants regardless of background.
Work location
Work model: On-site
260, North Columbus Street, Brandon Village, Bluemont, Ballston, Arlington, Arlington County, Virginia, 22203, United States
Arlington, Virginia
Key Responsibilities
- check_circleDesign and build dataset preparation pipelines for acquiring, cleaning, and versioning ML data
- check_circleEngineer features to extract meaningful signals from structured and semi-structured data sources
- check_circleDeploy models to production on cloud infrastructure and build pipelines for retraining and scoring
- check_circleMonitor model performance in production by tracking drift, false positive rates, and detection efficacy
- check_circleBuild and maintain batch and streaming data pipelines using Synapse, Fabric, Spark, and Event Hubs
- check_circleBuild dashboards and visualizations to communicate model outputs to technical and non-technical stakeholders
- check_circleCreate validation frameworks using synthetic test data generation and shadow-mode evaluation
- check_circleCollaborate with cross-functional teams to identify ML opportunities and translate operational problems into data solutions
- check_circleWrite and optimize analytical queries in SQL, KQL, and PySpark for data exploration and real-time analysis
- check_circleRun structured experiments to test algorithms, measure performance, and document findings
- check_circleTrain, evaluate, and tune ML models including regression, classification, and anomaly detection
Requirements
- verifiedBachelor's degree in computer science, data science, statistics, mathematics, or related quantitative field
- verified3–5 years of hands-on experience in data engineering, ML engineering, or applied analytics
- verifiedHands-on cloud platform experience (Azure or AWS)
- verifiedProficiency in Python
- verifiedStrong SQL skills
- verifiedExperience with version control systems (Git) and CI/CD practices
- verifiedExperience building data pipelines that handle batch and streaming workloads
Nice to Have
Experience with time-series analysis, anomaly detection, or statistical process control on operational data. Familiarity with unsupervised and semi-supervised techniques (isolation forest, clustering, ensemble methods). Experience building and managing ML model lifecycle on Azure (MLflow, Fabric ML, Azure ML) or AWS (SageMaker, Glue, Step Functions). Familiarity with KQL (Kusto Query Language) for time-series decomposition, log analytics, or real-time data exploration. Knowledge of data modeling and dimensional modeling concepts. Experience with synthetic test data generation and model validation frameworks. Familiarity with operations and monitoring of mission-critical data platforms.
Similar Job Opportunities
Skills, education and keywords
Skills: Machine Learning, Data Engineering, Azure, Aws, Python, SQL, Git, Ci/cd, Synapse, Fabric.
Education: Bachelor's degree in CS, Data Science, Statistics, Math, or related field (or equivalent experience).
Frequently asked questions about Software Engineer-Data Engineering, Machine Learning (ML) at AAMVA (American Association of Motor Vehicle Administrators)
What does a Software Engineer-Data Engineering, Machine Learning (ML) at AAMVA (American Association of Motor Vehicle Administrators) do?expand_more
A Software Engineer-Data Engineering, Machine Learning (ML) at AAMVA (American Association of Motor Vehicle Administrators) is responsible for the following: Design and build dataset preparation pipelines for acquiring, cleaning, and versioning ML data; Engineer features to extract meaningful signals from structured and semi-structured data sources; Deploy models to production on cloud infrastructure and build pipelines for retraining and scoring; and Monitor model performance in production by tracking drift, false positive rates, and detection efficacy.
What are the requirements for this Software Engineer-Data Engineering, Machine Learning (ML) role?expand_more
AAMVA (American Association of Motor Vehicle Administrators) is looking for candidates who meet the following requirements: Bachelor's degree in computer science, data science, statistics, mathematics, or related quantitative field; 3–5 years of hands-on experience in data engineering, ML engineering, or applied analytics; Hands-on cloud platform experience (Azure or AWS); Proficiency in Python; Strong SQL skills; and Experience with version control systems (Git) and CI/CD practices.
Where is the Software Engineer-Data Engineering, Machine Learning (ML) role at AAMVA (American Association of Motor Vehicle Administrators) located?expand_more
Software Engineer-Data Engineering, Machine Learning (ML) at AAMVA (American Association of Motor Vehicle Administrators) is based in 260, North Columbus Street, Brandon Village, Bluemont, Ballston, Arlington, Arlington County, Virginia, 22203, United States. This is a on-site role.
Is this Software Engineer-Data Engineering, Machine Learning (ML) job remote, hybrid, or on-site?expand_more
AAMVA (American Association of Motor Vehicle Administrators) has listed this Software Engineer-Data Engineering, Machine Learning (ML) role as on-site.
How much experience is required for this Software Engineer-Data Engineering, Machine Learning (ML) role?expand_more
Software Engineer-Data Engineering, Machine Learning (ML) at AAMVA (American Association of Motor Vehicle Administrators) typically requires 3–5 years of relevant experience at the mid level level.
What skills do you need for the Software Engineer-Data Engineering, Machine Learning (ML) role at AAMVA (American Association of Motor Vehicle Administrators)?expand_more
Key skills for Software Engineer-Data Engineering, Machine Learning (ML) at AAMVA (American Association of Motor Vehicle Administrators) include Machine Learning; Data Engineering; Azure; Aws; Python; SQL; Git; and Ci/cd.
What education is required for Software Engineer-Data Engineering, Machine Learning (ML) at AAMVA (American Association of Motor Vehicle Administrators)?expand_more
Educational requirements for this role: Bachelor's degree in CS, Data Science, Statistics, Math, or related field (or equivalent experience).
What category does the Software Engineer-Data Engineering, Machine Learning (ML) role belong to?expand_more
Software Engineer-Data Engineering, Machine Learning (ML) at AAMVA (American Association of Motor Vehicle Administrators) is part of the it job category on Recrutus.