Our OEM Client based in Whitley, Coventry, is searching for a Virtual Build Engineer to join their team, Inside IR35. This is a 12-month contract position initially until 31st March 2026, with the potential for further extensions. Umbrella Pay Rate: Up to £33.64 per hour. Our client has recently restructured the Propulsion CAE team in particular the Virtual Build Factory team. The area is currently inventing and developing its processes to improve speed & quality. The successful candidate will be required to detect opportunities and develop the code to automate its process to unleash the efficiency required from the team. The role is multidisciplinary as it involves working on-cycle and off-cycle programmes primarily developing the code but working closely with Development engineers, analysts and model builders. The individual will be responsible for the following: The collection and compilation of the Non-Geometric Data by working with a multitude of internal customers The collection and compilation of the Geometric Data operating the inhouse CAD Software to help the team build the virtual models. Understand the Virtual Factory floors in order to find opportunities to automate the current processes as well as build the required KPIs Determine the automation and optimisation requirements, develop code, metrics and targets. Code/program to convert the manual effort into automation Develop programming code to automate all manual processes to reduce time and improve quality. Support methods reviews as appropriate contributing ideas. Develop and deliver new process training material. Undertake any other work as directed by their line manager in connection with their job as may be requested. Creation of user guides and manuals to the train CAE team members. Essential: Proficiency in programming language Python, VB, Java, Simulink, Matlab etc Good understanding of CAD software 3DX CATIA MS Excel Ability to adapt / understand new technology areas Communication skills Desirable: Understanding of propulsion systems. Understanding of materials and material properties. Awareness of EDU, Batteries, HV charging system, Electrical, Mechanical Machine learning AI etc. ADZN1_UKTJ