Join a dynamic AI team as the embedded manufacturing expert, reviewing and improving AI-generated plans for processes like bill of process creation, DFM/DFA analysis, and production workflows. Provide hands-on feedback to refine models, ensuring they align with real-world manufacturing realities for complex hardware. This high-impact role shapes AI systems that transform how teams build physical products from prototype to production.
Key Responsibilities:
- Own and refine the manufacturing evaluation process by reviewing AI model outputs on real tasks and documenting failure modes.
- Assess AI-generated bills of process, DFM/DFA recommendations, inspection plans, tooling suggestions, and manufacturability reviews.
- Work hands-on in software to analyze customer manufacturing workflows, spotting gaps between AI proposals and practical production needs.
- Physically build, mock up, or validate suggested manufacturing processes, including sourcing and assembling parts to test real-world viability.
- Collaborate with AI engineers to convert manufacturing insights into training data, evaluations, and product enhancements.
- Act as the primary manufacturing authority for the AI team, guiding domain expertise needs and potentially coordinating external experts.
- Help define and evolve this new role based on highest-leverage contributions.
3-6 years of experience in manufacturing engineering or new product introduction, with hands-on work advancing electromechanical products from prototype to production.
Direct experience taking electromechanical products like robotics, drones, EVs, or aerospace hardware through production, not just coordinating with contract manufacturers.
Worked across multiple products or companies, owning manufacturing decisions end-to-end in startup or small-team settings.
Ability to read and interpret CAD/BOM packages and create a bill of process from scratch.
Hands-on DFM/DFA experience, including floor-level involvement and driving design changes.
BS in Mechanical, Manufacturing, or Industrial Engineering, or equivalent demonstrated hands-on background.
Preferred:
Background in high-tech manufacturing environments.
Experience using AI/LLM tools like large language models in technical workflows.
Proven ability to articulate manufacturing process successes and failures in structured feedback for non-experts.