Applied Machine Learning Engineer

Vulcan Elements is manufacturing American rare-earth permanent magnets for a secure, resilient future. With a focus on national security and economic resiliency, we serve critical industries such as defense, aerospace, and automotive, powering a high-technology future. Vulcan Elements is building a team of ambitious professionals committed to Mission Focus, Technical Excellence, and Transparency. 

As the Data Engineer, you will design and build the data infrastructure that makes Vulcan’s operational and business data useful — first at pilot scale, and then as the foundation for a 10,000 ton/year facility. You will work from architecture to implementation: evaluating and selecting platforms, designing data models and pipelines, and building the systems that collect, contextualize, and deliver data to the teams and tools that depend on it. You will collaborate closely with cross-functional stakeholders to translate operational requirements into a durable, scalable data architecture. As Vulcan grows, this role has the opportunity to expand into a team leadership position. 

This role begins in Durham, NC and is expected to move to Benson, NC upon completion of new facility.

• →Experience with time-series databases (InfluxDB, TimescaleDB, or similar) common in industrial and IoT environments 

• →Familiarity with industrial data concepts — historian data, process tags, OT/IT integration — and the data challenges specific to manufacturing environments 

• →Experience working on or alongside a Unified Namespace or MQTT-based data architecture; understands how industrial messaging infrastructure relates to the data layer 

• →Familiarity with data Lakehouse platforms and open table formats (Delta Lake, Apache Iceberg, or similar) 

• →Experience with ETL orchestration tooling (Airflow, Prefect, dbt, or similar) 

• →Comfort with scripting and lightweight development (Python, SQL, or similar) for pipeline development and data quality tooling 

• →Familiarity with cloud platforms (AWS, Azure, or GCP) and experience evaluating on-premises vs. cloud tradeoffs for data infrastructure 

• →Experience working in a controlled information environment; familiarity with the handling requirements for Controlled Unclassified Information (CUI) or export-controlled technical data under ITAR or EAR 

• →Experience in a manufacturing, industrial, or operations-heavy environment