Robotic Process Engineer - Aerospace & Defense
Quick Summary
About Machina Labs: Engineering moves at software speed. Manufacturing doesn't. Yet. Machina Labs is changing that. We build intelligent,
Engineering moves at software speed. Manufacturing doesn't. Yet.
Machina Labs is changing that. We build intelligent, software-defined factories that produce complex metal structures directly from digital design. By integrating advanced metal forming, robotics, and automated production inside a flexible factory architecture, we enable customers to move from prototype to production in weeks, not years.
Backed by Lockheed Martin, Toyota, and NVIDIA, we're building the manufacturing infrastructure that defense, aerospace, and advanced mobility programs will run on.
If you want to work on hard problems that matter and see them fly, drive, and defend, this is the place.
As a Robotic Process Engineer at Machina Labs, you will play a key role in enabling RoboForming, our robotic incremental sheet metal forming process, through CAD manipulation, robot tool path generation, and process optimization. You'll work with our Robocraftsman system and internal software stack to convert digital part designs into robotic tool paths, analyze scan and forming data, rapidly iterate on forming strategies based on real-world feedback, and support iterative development of forming strategies. This role is hands-on and collaborative, with a strong emphasis on digital tooling, data-driven improvement, and integration with advanced robotic systems.
This role will put you in charge of optimizing our manufacturing process to form sheet metal parts and assemblies for aerospace applications. Working directly with our customers to provide feasibility analysis, DFM reports, and production-ready first article components, you will be a leader in advancing our technology across the aerospace industry.
- Generate and modify CAD models for RoboForming.
- Use internal software stack to convert CAD into robot tool paths for execution on the Robocraftsman.
- Analyze RoboForming data and 3D scan results to assess part quality and identify areas for improvements.
- Design and execute structured experiments (DOE) to optimize forming parameters and tool path strategies.
- Collaborate with product managers, hardware development teams, software engineers, and manufacturing engineers to improve and develop new tools, workflows and tool path strategies.
- Contribute to technical discussions with external customers as needed to support project goals and ensure alignment
- Work autonomously and make informed decisions with limited data, then refining based on outcomes.
- Document process, results, and analyses for continuous improvement for internal use.
- B.S. in Mechanical, Manufacturing, Industrial, or Aerospace Engineering, or related field.
- 0-3 years of experience in manufacturing within a robotics or aerospace environment.
- Proficiency in at least one CAD software (e.g., SolidWorks, Catia, NX, Fusion 360, Rhino).
- Familiarity with CAM, tool path generation, or robot programming.
- Strong data analysis skills (e.g. MATLAB, Python, advanced Excel or similar tools).
- Comfort working in open-ended problem spaces, making rapid decisions and course corrections as needed.
- Strong attention to detail and ability to follow standard processes.
- Comfortable working in a hands-on, fast-paced manufacturing environment.
- Demonstrated ability to interface with interdisciplinary teams and internal/external project stakeholders.
- Effective written and verbal communication skills.
- Strong mentality toward safety and occupational hazard prevention.
- Full cycle development of a new product or process.
- Experience with Root Cause Corrective Action
- Expertise in CAD surface modeling.
- Experience working with industrial robots (FANUC, KUKA, ABB, etc.).
- Knowledge of CNC machining, additive manufacturing, or other digital manufacturing processes.
- Exposure to 3D scanning, inspection systems, or metrology tools.
- Experience with computational geometry.
Location & Eligibility
Listing Details
- Posted
- September 17, 2026
- First seen
- September 17, 2026
- Last seen
- September 17, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 67%
- Scored at
- September 17, 2026
Signal breakdown
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