Rapsodo is a leading global sports technology company where passion for performance meets cutting-edge innovation. We develop advanced analytics and hardware that empower athletes to play without limits™. As our QA Engineer Intern, you will fuel the next generation of products through rigorous testing, data-driven analysis, and cross-team collaboration, ensuring we deliver game-changing results.

About the role

We're building a high-speed sports robot and the validation system around it. A machine that moves this fast, this repeatably, throws off a steady stream of mechanical problems: reaction loads into the frame, dynamic balance, structural stiffness, resonance, fatigue, joint wear, fixture repeatability.

That's where you come in. We want someone who can model a mechanism before we build it, predict how it will behave, and then tell us honestly how far the prediction was off once we measure the real thing. You'll sit with the QA/Validation team, and simulation will be your main lever.

One concrete example of the work: the forward swing dumps significant reaction torque into the structure and shifts the system's center of gravity through the stroke. We want a counterweight / dynamic balancing scheme that cancels as much of that as possible. Model it, propose it, verify it against measured data. There are plenty more problems like it waiting.

You'll work across a mixed engineering team — mechanical, hardware, firmware, and software — so you'll be as involved in what the test system logs as in what the fixture is made of. Hands-on, on-site lab work, not a desk-only internship.

What you'll do

Simulation and analysis (the core of the role)

• Build multibody dynamics models of the robot's mechanisms; extract joint reaction loads, torques, and CG behavior across the motion profile
• Analyze dynamic balancing and counterweight concepts: mass, placement, linkage or counter-rotating approaches and quantify what each one actually cancels
• Run structural and modal FEA to find stiffness limits, resonances, and fatigue-critical features before they show up as a broken part
• Correlate every model against measured data. A simulation nobody validated is a guess with better graphics.

Validation and lab work

• Help build the robot validation tool, test fixtures, instrumentation, and the measurement setup behind it
• Instrument the robot and its rigs (load cells, accelerometers, encoders, high-speed camera targets) and turn raw signals into numbers the team trusts
• Run validation campaigns: performance verification, repeatability, durability and life cycling, tolerance checks, failure investigation
• Work with firmware and software engineers on test automation, data logging, and reporting
• Write test plans, validation protocols, and test reports; log and track defects
• Support design reviews with tolerance stack-ups, GD&T checks, and design-for-test input

Requirements

• Currently pursuing or recently completed a BS/MS in Mechatronics, Mechanical, or Robotics Engineering (or equivalent)
• Available full-time in Singapore for at least 6 months
• Strong grounding in dynamics, mechanism kinematics, and vibration fundamentals, you should be comfortable reasoning about inertia, reaction loads, and natural frequencies
• Hands-on experience with at least one simulation tool and a willingness to go deep on it
• CAD proficiency ([SolidWorks / Fusion 360 / NX])
• Comfortable with lab instrumentation and data acquisition, can wire up a sensor and sanity-check the number that comes out
• Able to work alongside hardware, firmware, and software engineers and speak enough of their language to be useful
• Writes clearly. Analysis nobody can read is analysis nobody will act on.
• Careful and safety-conscious around high-energy moving machinery

Strong plus

• Multibody dynamics simulation, such as MSC Adams, Simscape Multibody, RecurDyn, Ansys Motion, or equivalent — able to model a driven linkage and pull out joint reaction loads over a full motion cycle
• Experience with dynamic balancing / counterweight design, inertia and CG management, or vibration and modal analysis
• FEA beyond coursework: structural, modal, fatigue, or explicit dynamics
• Python or MATLAB for data processing, model post-processing, and test automation
• High-speed video motion capture or strain gauge work
• Exposure to servo/actuator systems, motor sizing, or control-system basics
• Interest in sports technology

What you'll get

• Real, unsolved mechanical problems with measurable answers — your model either predicts what the machine does or it doesn't, and the data will say so
• Ownership of analysis and tooling the team will keep using after you leave
• Mentorship from [senior validation / mechanical engineers]
• The full loop: model, design, build, test, iterate  on production sports-tech hardware, next to every engineering discipline that touches it