Cloud ML Engineer: Data Pipelines & Anomaly Detection

AAMVA (American Association of Motor Vehicle Administrators); Arlington (VA); Hybrid; USD 90,000 - 130,000; Full time

Job summary

AAMVA (American Association of Motor Vehicle Administrators) is looking for a skilled Machine Learning Data Engineer to develop and operationalize ML solutions using cloud infrastructure (Azure or AWS). This role involves the full model lifecycle, from dataset preparation to deployment and performance monitoring.

The ideal candidate will have a Bachelor’s degree in a quantitative field and 3–5 years of hands-on experience in data engineering and machine learning. Strong communication skills and the ability to work with cross-functional teams are essential.

Qualifications

• 3–5 years of experience in data engineering, ML engineering, or applied analytics.
• Proficiency in Python for data processing and ML model development.
• Experience building data pipelines that handle batch and streaming workloads.

Responsibilities

• Designing and building dataset preparation pipelines for ML.
• Training, evaluating, and tuning ML models.
• Deploying models to production on cloud infrastructure.

Skills

Data engineering

Machine learning

Python

SQL

Cloud platform experience (Azure or AWS)

Feature engineering

Data pipelines

Statistical analysis

Problem-solving

Communication skills

Education

Bachelor's degree in computer science, data science, or related field

Tools

Azure Synapse Analytics

Apache Spark

Power BI

Git

Job description

AAMVA (American Association of Motor Vehicle Administrators) is looking for a skilled Machine Learning Data Engineer to develop and operationalize ML solutions using cloud infrastructure (Azure or AWS). This role involves the full model lifecycle, from dataset preparation to deployment and performance monitoring.

The ideal candidate will have a Bachelor’s degree in a quantitative field and 3–5 years of hands-on experience in data engineering and machine learning. Strong communication skills and the ability to work with cross-functional teams are essential.