Intelliswift, an LTTS Company, is seeking a Mechanical Engineer II to help shape the future of AI-enabled engineering workflows. The role involves evaluating and validating AI-generated solutions for mechanical design and analysis while collaborating with research and engineering teams to improve engineering workflows.
Responsibilities:
- Evaluate AI-generated mechanical designs, simulations, and engineering analyses for technical accuracy and practical feasibility
- Assess manufacturability, performance, reliability, and design trade-offs across a variety of engineering challenges
- Develop engineering tasks, test cases, benchmarks, and validation methodologies used to evaluate system performance
- Provide expert feedback on mechanical engineering best practices and design principles
- Collaborate closely with researchers, software engineers, and cross-functional partners to improve engineering workflows
- Analyze failure cases and help identify root causes and corrective actions
- Ensure engineering solutions align with established standards, safety requirements, and documented processes
- Create clear technical documentation and communicate findings to both technical and non-technical stakeholders
Requirements:
- Bachelor's degree in Mechanical Engineering or a related engineering discipline
- 3–5+ years of practical mechanical engineering experience
- Advanced proficiency with one or more industry-standard CAD and simulation tools such as: SolidWorks, Siemens NX, CATIA, Autodesk Inventor, Creo, FreeCAD, Ansys
- Strong knowledge of multiple mechanical engineering disciplines, including: Thermodynamics, Fluid Mechanics, Heat Transfer, Structural Analysis, Mechanical Design, Manufacturing Processes
- Experience working in cross-functional environments and communicating complex technical concepts to diverse audiences
- Ability to manage multiple priorities and work effectively in a fast-paced environment
- Experience with Python, MATLAB, or other scripting tools
- Experience automating engineering workflows or analyzing engineering datasets
- Familiarity with simulation-driven design, testing, validation, or product development processes
- Experience supporting multidisciplinary engineering teams