Slip Robotics
Staff Mechanical Engineer
Norcross, Georgia, United States · Staff+
Sponsorship not specifiedDetected 91 days ago
LogisticsSolidWorksFEARoboticsMechanical DesignCommunicationMentoringTolerance Analysis
About the role
- Introduction Slip Robotics is a pioneering Series B startup transforming the logistics and freight industries through advanced autonomous mobile robotics.
- Our SlipBots automate the loading and unloading of semi-trailers, drastically improving efficiency, safety, and reliability in freight operations.
- Our systems are already trusted by some of the most recognizable names in automotive and e-commerce.
Responsibilities
- Own mechanical architecture decisions and lead the design of key subsystems for autonomous mobile robots.
- Serve as the technical lead across multidisciplinary teams to ensure mechanical, electrical, and software integration.
- Spearhead the design and deployment of new hardware capabilities for cargo handling and storage on and above the robot platform.
- Lead the transition from prototype to production, developing scalable, cost-effective, and reliable systems.
- This is a critical role for a senior individual contributor who will drive the mechanical architecture of our flagship robot platforms.
- You'll be responsible for taking complex systems from concept through high-volume production, leading technically across projects, and shaping the long-term direction of Slip's hardware design.
Requirements
- Bachelor's or Master's degree in Mechanical Engineering or a related field.
- Proven track record of delivering complex, production-ready hardware in a fast-paced, hands-on environment.
- Expertise in CAD (e.g., SolidWorks, Onshape, PDM), FEA/simulation, tolerance analysis, and DFM/DFA practices.
- If you are a highly skilled Staff Mechanical Engineer passionate about robotics and wish to contribute to a dynamic team working on cutting-edge technology, we would love to hear from you!
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This listing is sourced directly from Slip Robotics's careers page and normalized into a canonical job model.