About the Team:
The Relativity Space NDE Engineering Team is dedicated to the integrity of our product while tackling the challenges of our traditional and non-traditional manufacturing methods. We are tasked with developing and executing inspection of a huge variety of materials and components using cutting-edge industry technology and vetting, developing, and deploying automation, machine learning and Statistical Process Control solutions to achieve continuous improvement in efficiency and execution. From designing novel in-house systems and processes that adhere to industry standards, to executing challenging technical inspection operations, our team maintains a steadfast commitment to integrity, efficiency, accuracy, and reliability.
About the Role:
Your core responsibilities will be:
• Coordinate with process stakeholders, identify applicable external resources, and develop infrastructure to unify manufacturing, quality, and NDE data into central minable database • Reduce human factors as feasible through automation in data collection (e.g. scanning, instrument setup, etc.), data routing, and decision making • Demonstrate correlation and automated prediction capability between manufacturing defects and process inputs. Demonstrate ability to prevent defects from forming • Certify proof-of-concept with customers • Work closely with NDE Level 3s and NDE Engineers to develop and execute feasibility studies, POD's, and qualification plans incorporating the above • Interface with outside stakeholders to ensure that qualification data and documentation is in compliance with applicable external customer's specifications and/or facilitate and document acceptable alternative methodologies (audit proof) • Engage in proactive mentorship and provide training and oversight for less experienced Engineers
About You:
BS or MS in an engineering related field
5+ years of relevant experience involving NDE methods and acceptance criteria
Track record of delivering technically concise reports to external and/or internal engineering stakeholders utilizing multiple data sources
Demonstrated ability to apply engineering fundamentals to achieve a practical manufacturing/production outcome, or similar relevant scope
Technical knowledge in at least 1 of the following NDE Methods:
• Digital RT • CR • ECA • PAUT
Understanding of welding flaw acceptance criteria
Nice to haves but not required:
• M.S. and/or PHD in Engineering with a focus on one or more NDE methods • Experience performing statistical analyses including linear and multi-linear regression, Guassian and Bayesian probabilities using R or Python • Verifiable experience contributing to design and/or qualification of automated NDE systems • Working knowledge of Lean Manufacturing principles and familiarity with MES systems • Exposure to aerospace industry codes and standards • Experience with one or more CAD modeling software platforms • Previous or current Level 2 or 3 certification in any of the following NDE Methods: Digital RT, CR, ECA, PAUT • Current ASNT Level 3 in one or more methods • Experience with inspection of additively manufactured materials, FSW's, and OTW's • Experience Auditing 3rd Party NDE service providers and equipment vendors • Competency in advanced NDE data analysis in one or more methods (PAUT, ECA, CT, DR, FMC/TFM)