Virtual Analysis Engineer Safety Biomechanics
RLE India Private Limited•Chennai
•full time Essential: • 1-4 years of automotive CAE experience, with a focus on vehicle crashworthiness and occupant-restraint-system development. • 1-2 years of foundational hands-on experience in developing and integrating safety FE models at full-vehicle, subsystem, and component levels, including restraint systems. • Proficiency in PRIMER, ANSA, and LS-DYNA are mandatory. • Strong engineering fundamentals, including a sound understanding of classical and applied mechanics and the operation of basic restraint systems such as single-stage airbags and seatbelts with constant force retractors. • Strong logical reasoning to predict, analyze, and troubleshoot complex nonlinear crash events. . Desirable: • Exposure to Human Body Model (HBM) simulations at sled or vehicle level. • Experience with Linux scripting, Python, Jupyter Notebook, and AI tools. • Good working knowledge of metals, composite components, and failure analysis. • Understanding cross-functional performance requirements. • Experience developing design proposals and collaborating with design engineers to implement them. • Experience working with automotive OEMs in vehicle safety. Key Responsibilities & Tasks • Develop sled buck models from full-vehicle structural models and integrate restraint-system models. • Set up simulation decks with occupants for frontal or side-impact scenarios. • Perform 100ms debug simulations with minimal support. • Load multiple animations, independently complete visual assessments of results, and generate all required plots using the MetaPost OIC toolbar. • Prepare occupant-simulation reports for frontal or side-impact load cases. • Assess and refine model and result quality, ensuring all evaluations are completed on schedule to support project timelines. • Participate in design reviews and recommend improvements to occupant and restraint-system performance. • Collaborate with team members and regularly communicate project updates, findings, and lessons learned during daily virtual or in-person meetings.
