Industrial Designer
About the role
Industrial Designer for wearable hardware platform at Human Archive, a robotics data lab focused on embodied intelligence. Role involves shaping visual language, ergonomics, and user-facing identity of wearable system; collaborate with engineering and manufacturing teams in SF.
Responsibilities
- Develop and iterate on the visual and ergonomic design language of the wearable system — form, finish, material palette, and user interaction.
- Create high-quality concept sketches, 3D renderings, and physical models to communicate design intent to engineering and leadership.
- Collaborate with the mechanical engineer (India) to ensure design intent is preserved through the engineering and fabrication process.
- Contribute to user research and wear testing, translating real feedback into design refinements.
- Maintain a living design system — material specs, finish standards, CMF documentation — that guides vendor conversations and future iterations.
- Design packaging, unboxing experience, and product presentation materials as needed.
Qualifications
- Bachelor's degree in Industrial Design, Product Design, or equivalent — recent graduates (2023-2025) strongly encouraged.
- Strong portfolio demonstrating concept-to-prototype capability, ergonomic thinking, and high visual craft.
- Proficiency in CAD tools (Fusion 360, Rhino, or similar) and rendering software (KeyShot, Blender, or equivalent).
- Ability to communicate design intent clearly through sketches, renders, and physical models.
Skills
About Human Archive
Multimodal data provider for robotics and world modeling
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.
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- QA / Hardware Test Engineer3mo agoHybrid (San Francisco, CA) · Engineering
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