Description This role is categorized as hybrid. This means the successful candidate is expected to report to Austin Technical Center three times per week, at minimum [or other frequency dictated by the business if more than 3 days]. The Role We are looking for a hands-on Machine Learning Engineer with at least seven years of experience to productionize machine learning for manufacturing and to build the data engineering that those models depend on.
This person will design, train, validate, and deploy models, and will design and operate the ETL/ELT pipelines, feature data, and governed Bronze, Silver, and Gold products those models run on. Current, working knowledge of Databricks is required. What You'll Do Productionize manufacturing machine learning, including training, validation, batch scoring, deployment, monitoring, and retraining workflows in Databricks.
Design and build the data engineering underneath those models: ingestion, transformation, curation, feature pipelines, and governed tables and volumes in Unity Catalog. Build reusable Bronze, Silver, and Gold pipelines and medallion patterns that analytics and ML both consume. Use M
Lflow and Unity Catalog for experiment tracking, model registration, versioning, lineage, and controlled promotion across environments. Ingest from enterprise and plant sources with managed connectors, DLT, Auto Loader, and structured streaming where those fit. Partner with data science, architecture, product, manufacturing, and platform team