Mechanical Engineer - Mobile Manipulator Design (MoMa) | Apprentice at Origin

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

15 May, 26

Salary

0.0

Posted On

14 Feb, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Mechanical Design, Dynamic Analysis, Kinematic Analysis, Stability Analysis, CAD, FEA, GD&T, Tolerance Stack-up, Robot Kinematics, Robot Dynamics, Structural Analysis, Prototyping, DFMEA, V&V Protocols, URDFs, SolidWorks

Industry

Robotics Engineering

Description

As a Mechanical Engineer – Mobile Manipulator (MoMa) Design Apprentice at Origin (formerly 10xConstruction), you will play a key role in building the next generation of construction robotics. You will contribute to the core mechanical architecture of our robot, enabling general-purpose construction tasks through superior dynamic stability, structural integrity, and maneuverability. This is a high-ownership apprenticeship role where you will work closely with cross- functional teams to take designs from concept to prototype to deployment. Key Responsibilities MoMa Design & Analysis Architect and design core mechanical systems of the mobile manipulator focused on strength, stability, and maneuverability. Perform dynamic, kinematic, and stability analyses (reach, payload, tip-over, etc.) to ensure safe and efficient operation. Define and benchmark performance metrics for general-purpose construction tasks: tool compatibility, reachability, maneuverability, stability. Define and analyze tool and sensor coverage maps and optimize navigation limits. Component Integration & Calibration: Lead mechanical design for mounting key components including actuators, sensors, and compute modules. Design and implement calibration jigs, fixtures, and measurement protocols. Manage manufacturing tolerances and stack-up to ensure precision and alignment. Systems Engineering & Verification & Validation (V&V): Translate product requirements into verifiable engineering requirements for stability, integrity, and performance. Develop and execute V&V protocols for MoMa subsystems. Lead DFMEA, risk analysis, and mitigation for the platform. Prototyping & Fabrication: Drive prototyping strategies using aluminum extrusions, 3D printing, and laser cutting. Work hands-on in the hardware lab using tools (drills, grinders, etc.) to build and iterate quickly. Real-to-Virtual Fidelity & Collaboration: Create high-fidelity URDFs (kinematics, collision zones, inertial properties) from CAD. Define and manage tolerance stack-ups and inertial properties for simulation accuracy. Collaborate with controls, embedded, and software teams for smooth integration. Graduates only Relevant work experience: >6 months. Bachelor’s or Master’s degree in Mechanical Engineering, Robotics, or related field. Proficiency in CAD tools (SolidWorks, Inventor, etc.). Knowledge of FEA tools, GD&T, and tolerance stack-up analysis. Strong fundamentals in robot kinematics, dynamics, and structural analysis. Exposure to manufacturing processes, material selection, and prototyping. Strong communication and problem-solving skills. Preferred Qualifications Portfolio of mechanical/robotics projects. Patents or publications in robotics / automation / related domains. Hiring Note This is an Apprentice position. We are looking for Immediate Joiners (or candidates with minimal notice period). Why Join Origin Work on real-world robotics problems with direct impact. Own end-to-end mechanical development: design → build → test. Learn in a fast-paced environment with a strong technical team. Help build robotics that can transform the construction industry.

Responsibilities

The apprentice will architect and design core mechanical systems for the mobile manipulator, focusing on strength, stability, and maneuverability, while performing dynamic and kinematic analyses to ensure safe operation. Key duties also involve leading mechanical design for component integration, developing V&V protocols, and driving prototyping strategies using various fabrication methods.