> Markdown version of [/jobs/ext/3760220-ai-ml-data-platform-engineer](https://www.wearedevelopers.com/jobs/ext/3760220-ai-ml-data-platform-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Data Platform Engineer - **Company:** ePace Technologies Inc - **Location:** Baltimore, MD, United States - **Experience:** Experienced - **Contract:** Contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Microsoft Azure, BigQuery, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Vault Modeling, Python (Programming Language), Machine Learning, Tensorflow, Service Design, Software Engineering, SQL Databases, Data Streaming, Workflow Management Systems, Data Processing, Google Cloud, Feature Engineering, Pytorch, Snowflake, Model Validation, Event Driven Architecture, Scikit Learn, Information Technology, Star Schema, Apache Kafka, Data Management, Video Streaming, Restful APIs, Data Pipelines, Amazon Redshift, Databricks - **Published:** October 15, 2026 - **Apply:** https://www.dice.com/job-detail/f628dece-3324-469c-ba35-660f9526343a ## About the Role 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 Google Cloud Platform 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.