AI/ML Data Platform Engineer

Rate: $55-60/hr C2C

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Position 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. xhqgsiq
• Data governance, privacy, and security requirements.