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Mecka AI is building the data infrastructure layer for robotics and embodied AI. The company designs and operates global systems for data capture, data labeling, and hardware-enabled workflows used by leading AI labs and robotics companies to train and validate humanoid and embodied AI systems.
In this role, you will own mechanical parts and assemblies from CAD through prototype testing and supplier feedback. You'll design hardware that holds sensors in precise alignment, withstands repeated use, remains comfortable for field operators, and manages thermal challenges effectively. Your designs will directly impact how Mecka's capture systems perform in real-world deployment.
Key responsibilities include:
- Designing mechanical systems that support accurate recording while remaining easy to assemble, maintain, and manufacture.
- Building and testing prototypes to optimize fit, weight distribution, stiffness, and user experience.
- Analyzing tolerances, loads, and sensor alignment; validating assumptions through physical measurement and testing.
- Collaborating with electrical and sensor engineers on packaging, thermal management, cable routing, and service access.
- Engaging with suppliers to refine designs based on assembly results, reliability testing, and field feedback.
This is a hands-on role where you'll move quickly from concept to physical validation, working closely with robotics teams and frontier AI labs.
REQUIREMENTS:
Must-have:
- 3–4 years of mechanical engineering experience
- Proficiency in 3D CAD (SolidWorks, Onshape, or equivalent) and ability to produce clear engineering drawings
- Solid understanding of mechanics, materials, tolerances, fits, fasteners, and dimensional inspection
- Hands-on experience building prototypes and testing physical assemblies
- Knowledge of manufacturing processes (machining, molding, sheet metal, additive manufacturing)
- Experience packaging electronics and sensors with assembly, thermal behavior, and maintenance in mind
- Experience working with suppliers on part quality, manufacturability, and cost issues
Nice-to-have:
- Experience with wearable products, robot end effectors, handheld mechanisms, or precision sensor mounts
- Experience with flexible materials, thermal analysis, or fatigue and durability testing
