Senior Data Engineer, Research Delivery

Role overview Move complex AI security and data science methods from research prototypes into reliable production systems that can process customer data at scale. You’ll partner with researchers and engineers, own the technical handoff for demanding components, and help align research priorities with customer and product needs.

Responsibilities - Take advanced data science components from prototype through production design, performance tuning, and ongoing maintenance. - Address scale challenges in clustering and similarity analysis across large document and embedding collections. - Coordinate progress, readiness, and blockers between research and engineering teams. - Establish practical handoff standards for reproducibility, testing, and documentation. - Prioritize engineering work with customer and product requirements in mind.

Requirements - At least seven years building production data systems or data-intensive software, including putting research or data science code into production. - Strong Python skills and experience with distributed data processing. - Ability to profile and optimize workloads that exceed the capacity of a single machine. - Hands-on experience with clustering, nearest-neighbor search, or embedding-based approaches at scale. - Experience with vector databases, retrieval-augmented generation pipelines, or large-scale document processing. - Strong written communication across research and engineering teams, and U.S. citizenship.

Nice to have Experience on an applied research team, such as a machine learning research group.

Benefits and work setup Full-time, hybrid in Charlottesville, Virginia, or remote in the Eastern time zone. Compensation is listed up to $165,000.