Simulation/CAE-heavy mechanical engineering Expert

Requirements

• Extensive hands-on experience in simulation and CAE-heavy mechanical engineeringMust
• Proficiency with AI coding agents (Codex, Claude Science, Claude Code, Claude Cowork)Must
• Demonstrated ability to apply AI agents to complex engineering challenges and large-scale debuggingMust
• Exceptional written and verbal communication skillsMust
• Active involvement in current STEM fields with AI agentics as practical engineering tool
• Experience documenting technical workflows and providing actionable insights for technology improvement
• Familiarity with broader landscape of AI-driven engineering tools
• Track record of experimentation and adaptation to new technologies

What you'll do

• Experience navigating large codebases using AI agents
• Develop end-to-end engineering solutions using AI-generated code sequences
• Document and articulate real-world AI agent applications in CAE and mechanical simulation workflows
• Analyze engineering problems and design challenges addressed using AI-generated code
• Provide written and verbal feedback on AI tool performance and limitations in CAE domain
• Curate representative examples and scenarios illustrating advanced technical workflows with AI agents
• Translate complex technical workflows into clear, concise documentation for AI training insights
• Collaborate asynchronously with project leads through clear communication channels
• Ability to articulate approach, rationale, and complexity behind engineering examples

About the role

Role Title: simulation/CAE-heavy mechanical engineering Expert Role Type: Contractor Location: Remote micro1 is engaging simulation/CAE-heavy mechanical engineering Experts to contribute their technical expertise to a dynamic customer project focused on leveraging advanced AI agents in real-world scenarios. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. This opportunity is ideal for STEM professionals with deep experience in simulation and CAE, especially those who have adopted AI coding agents as integral tools in their workflows. Scope of Work • Provide detailed walkthroughs of how you employ AI coding agents such as Codex, Claude Science, Claude Code, and Claude Cowork in complex mechanical engineering simulation and CAE tasks. • Demonstrate and document real-world applications where AI agents are used for navigating large codebases, debugging challenging issues, or developing end-to-end solutions—not just basic coding assistance. • Describe and analyze the types of engineering problems, design challenges, or architectural changes addressed using AI-generated code sequences. • Contribute written and verbal feedback about the performance and limitations of AI tools within the CAE and mechanical simulation domain. • Curate representative examples and scenarios that illustrate advanced technical workflows involving AI agents, focusing on sequence generation rather than chatbot-style interactions. • Articulate the approach, rationale, and complexity behind selected examples to provide actionable insights for the AI training process. • Collaborate asynchronously with project leads and share input through clear and effective communication channels. Preferred Qualifications • Extensive hands-on experience in simulation and CAE-heavy mechanical engineering assignments. • Proven proficiency with Codex, Claude Science, Claude Code, and Claude Cowork as coding sequence generators in technical scenarios. • Demonstrated ability to apply AI agents to sophisticated engineering challenges—including navigating ambiguous requirements, large-scale debugging, or architectural overhauls. • Exceptional written and verbal communication skills, with the ability to translate complex technical workflows into concise documentation and feedback. • Active involvement in current STEM fields, using AI agentics as a practical extension of real-world engineering problem-solving. • Experience documenting technical workflows and providing actionable insights for technology improvement or training purposes. • Familiarity with the broader landscape of AI-driven engineering tools and a track record of experimentation and adaptation to new technologies. Originally posted on Himalayas