AI/ML Data Platform Engineer
Rate: $55-60/hr C2CPosition Overview:
The AI/ML Data Platform Engineer will design, build, and maintain reusable data products, pipelines, APIs, and AI-enabled data services supporting state government analytics and AI/ML initiatives. The role focuses on data integration, real-time streaming, data quality, governance, feature engineering, and ML model integration.
Key Requirements:
5+ years of experience in data engineering, software engineering, or ML engineering, including 2+ years in data product or data service design.
Bachelor's degree in Computer Science, Data Science, Engineering, or a related field; master's degree or PhD preferred.
Strong proficiency in Python and SQL.Experience developing production-quality ETL/ELT pipelines.
Hands-on experience with AWS, Azure, or GCP data platforms, including Amazon Redshift, BigQuery, Snowflake, Databricks, or equivalent services.
Experience with Apache Kafka, AWS Kinesis, Google Pub/Sub, Azure Event Hubs, or equivalent streaming technologies.
Familiarity with Apache Airflow, dbt, Prefect, or similar orchestration tools.
Understanding of star and snowflake schemas, medallion architecture, and data vault.
Experience designing REST APIs and working with event-driven architectures.
Understanding of ML fundamentals, feature engineering, data manipulation, exploratory data analysis, model evaluation, and deployment.
Familiarity with PyTorch, TensorFlow, or scikit-learn.
Experience with data quality, pipeline monitoring, troubleshooting, and incident resolution.
Strong analytical, problem-solving, communication, and collaboration skills.
Preferred Experience:
Great Expectations, Soda, or dbt tests.
Apache Atlas, DataHub, or Collibra.
Feature stores such as Feast or Tecton.
Integrating ML model outputs into data pipelines and data products.
Terraform and infrastructure as code.
Government, public sector, or regulated data environments.
Data governance, privacy, and security requirements.