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.

Responsibilities 

Architecture & Platform Design 

• Design and own Vulcan’s data architecture from operational data stores through ETL pipelines to the analytics and AI layer 

• Evaluate and select platforms for the data Lakehouse, ETL tooling, and operational databases, weighing scalability, compliance requirements, operational burden, and cost 

• Review, refine, and implement data architecture design documents, ensuring designs are technically sound and account for CUI and ITAR data handling requirements 

• Make and document key platform and design decisions with enough clarity that future team members can understand the reasoning and build on it 

• Ensure the architecture scales from pilot plant to full-scale facility without fundamental redesign 

• Apply sound engineering practices to everything you build: version control, testing, observability, and documentation, and hold those standards as the data team grows 

Data Pipeline & Integration 

• Design and build ETL pipelines that move data from operational data stores into the data Lakehouse with full contextual enrichment, making it ready for analytics and AI workloads 

• Build reliable ingest paths for structured data, time-series data, files, images, and other outputs from manufacturing and lab systems 

• Collaborate across engineering, operations, and IT to understand data flows, dependencies, and i