Mechanical Engineer - Wearable Systems

at Human Archive — Multimodal data provider for robotics and world modeling

INFull-time3+ years₹1.8M - ₹3M INRYC-W26

What the role involves

About Human Archive

Human Archive is a robotics data lab founded by Stanford and UC Berkeley dropouts. We work alongside frontier robotics labs and foundation model research groups to collect large-scale, real-world, annotated multimodal datasets of humans performing everyday tasks across household and industrial environments.

We are lean, technical, and operate at extreme speed, taking on unglamorous and conventionally impossible problems that directly unlock step-function gains in model capability.

The deployment of capable humanoids at scale will permanently redefine human labor. Undesirable physical work will disappear, and human effort will shift toward a new era of abundant creativity. This shift is inevitable, and we are building the infrastructure to accelerate it.

We are assembling the best team to solve the hardest problems in embodied intelligence. You will own meaningful systems from day one and see your work directly impact model capabilities. This is a once-in-a-generation inflection point. If you want to leave your dent on humanity and reshape physical labor markets forever, join us!

About the Role

You will design and build the physical architecture of a load-bearing wearable system — enclosures, mounting structures, modular docking mechanisms, and cable routing — with direct technical direction from the Head of Engineering.

This is a hands-on, execution-focused role. You will prototype fast, iterate based on real wear testing, and maintain high standards of mechanical quality and repeatability.

Responsibilities

Design adjustable, load-bearing wearable structures that accommodate a range of body sizes, optimizing for comfort and fatigue reduction during extended use

Develop protective enclosures and mounting systems for embedded electronics, balancing structural integrity with weight constraints

Design modular docking and retention mechanisms for removable hardware modules, including blind-mate alignment and tool-less serviceability

Iterate rapidly using 3D printing and small-batch fabrication; own hands-on testing and mechanical debugging

Collaborate with local fabrication and soft goods vendors to improve manufacturability

Define cable routing and strain management systems that survive repeated flexion and allow removal for cleaning

Required Qualifications

3-5 years of mechanical design or hardware prototyping experience

Strong proficiency in Fusion 360 or SolidWorks

Experience designing enclosures, structural mounts, or load-bearing assemblies

Hands-on prototyping experience with real-world durability and motion constraints

Preferred Qualifications

Experience in wearable hardware, robotics, drones, or embedded systems packaging

Familiarity with soft goods integration, battery enclosure design, and thermal considerations

Experience designing for field or industrial deployment environments

To Apply

Resume (PDF)

Portfolio or GitHub (if applicable)

About Human Archive

We’re archiving the physical world for embodied intelligence by collecting and labeling aligned multimodal data. To build dexterous and perceptive robots that generalize robustly, we need massive amounts of real-world data across multiple modalities and environments. We have thought deeply about the fine line between biomimicry and its application to humanoid systems. Based on this research, we design and deploy custom hardware across residential and manufacturing settings. We then post-process the resulting data through internal QA, anonymization, and annotation pipelines to deliver diverse, high-fidelity datasets at scale to frontier labs developing robotics foundation models and general-purpose robotics companies. We believe we are at a historic inflection point, with a unique opportunity to leave a dent on humanity and reshape physical labor markets forever. That's why our team dropped out of Stanford and Berkeley and moved to Asia to collect the world’s largest annotated multimodal dataset.

Full Human Archive profile

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