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Location: San Francisco ABOUT HUMAN ARCHIVE Human Archive is a research lab backed by Y Combinator focused on modeling human embodied intelligence. Humans are the most sophisticated biological systems we have ever observed, yet we still do not fully understand ourselves. Research into human physical intelligence — including the human hand, proprioception, and vision — remains largely unsolved. Our mission is to recover human embodied intelligence as a learned model. To achieve this, we build custom hardware products, deploy them globally at scale, and publish research. Today, our data is used for robotics and world modeling, but the broader opportunity is advancing scientific research into intelligence itself. Founded by Stanford and UC Berkeley researchers, we are lean, deeply 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. We are building the infrastructure to accelerate that transition by assembling the Human Archive mafia. 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 help reshape physical labor and work on problems that matter at civilizational scale, join us. THE OPPORTUNITY As a Research Engineer, you’ll work on multimodal sensing systems and sensor fusion research for embodied AI and robotics. This role sits at the intersection of robotics, perception, hardware systems, and machine learning, where your work directly shapes how multimodal data is collected, synchronized, fused, and used for downstream VLA training. You’ll research emerging sensing technologies across RGB-D video, motion capture, IMUs, tactile sensing, audio, and wearable systems, and study how different sensor combinations impact robot learning, policy performance, and generalization. You’ll work closely with hardware, ML, and research teams to design experiments, evaluate new sensing stacks, and help define the next generation of multimodal robotics datasets. Your work will help shape how frontier labs and leading robotics companies train their models, transforming physical labor markets and economies while contributing to broader research into human embodied intelligence. WHAT YOU’LL DO - Evaluate how different sensor modalities impact VLA training and downstream robotics performance - Work across RGB-D video, IMUs, motion capture, tactile sensing, audio, and wearable systems data - Design experiments around synchronization, calibration, fusion, and multimodal alignment - Prototype quickly and iterate from real-world robotics deployments and research feedback - Collaborate closely with hardware, ML, and research teams on next-generation sensing systems WHAT WE’RE LOOKING FOR - Master’s or PhD in robotics, computer vision, sensing systems, or related fields - Published research in sensor fusion, perception systems, multimodal datasets, or embodied AI - Strong technical intuition around hardware systems and robot learning - Experience with RGB-D video, IMUs, motion capture, tactile sensing, or robotics systems - Experience with reinforcement learning, real-world robot deployments, and how data impacts downstream policy performance - Highly curious, execution-oriented, and comfortable operating from first principles

Location: China Workplace: OnSite ABOUT HUMAN ARCHIVE Human Archive is a research lab backed by Y Combinator focused on modeling human embodied intelligence. Humans are the most sophisticated biological systems we have ever observed, yet we still do not fully understand ourselves. Research into human physical intelligence — including the human hand, proprioception, and vision — remains largely unsolved. Our mission is to recover human embodied intelligence as a learned model. To achieve this, we build custom hardware products, deploy them globally at scale, and publish research. Today, our data is used for robotics and world modeling, but the broader opportunity is advancing scientific research into intelligence itself. Founded by Stanford and UC Berkeley researchers, we are lean, deeply 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. We are building the infrastructure to accelerate that transition by assembling the Human Archive mafia. 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 help reshape physical labor and work on problems that matter at civilizational scale, join us. HARDWARE SUPPLY CHAIN LEAD (SHENZHEN) The most important operational role on the hardware program. You live in Shenzhen, walk the factory floor, and own the ODM relationship and the component supply. What you'll work on ODM relationship and program management - Day-to-day relationship with our manufacturing partner - SOW, milestone schedule, and deliverable tracking - On-site issue resolution at the factory - Contract negotiations and quarterly reviews Component sourcing - Allocations for critical components (industrial image sensors, IMUs, MEMS sensors, lenses, Li-ion cells) - Pricing, lead times, MOQs across the Chinese supply chain - Backup supplier lists for every critical part - Long-lead component buffer management Factory operations - In-person factory visits, line audits, first-article inspections, NPI runs - Floor QA and incoming material inspection - Yield improvement and corrective action plans - Translation between English-speaking engineering and Mandarin-speaking factory teams DFM and manufacturing liaison - DFM reviews between our engineering team and the ODM's process engineers - Test fixture and assembly line design - Real-time production blocker resolution Commercial and compliance - Contracts, NDAs, IP protection arrangements with Chinese partners - BOM cost tracking and cost-down sweeps - FCC, CE, RoHS, REACH documentation Required experience - Mandarin-native plus business-fluent English - Resident in Shenzhen or willing to relocate - 5+ years in hardware supply chain or ODM management roles in China - Deep working network across the Chinese consumer electronics supply chain - Comfortable on factory floors and in vendor meetings, not just on email Strong plus - Background at a hardware company building head-worn, body-worn, or consumer camera products (DJI, Insta360, GoPro, Meta, Anker, Goertek, etc.) - Sony industrial sensor allocation experience - Prior relationships at Tier-1 Chinese ODMs - Scaling hardware from <100 to 10,000+ units/year About this role You're our senior presence in China from day one. Supply chain runs on trust and proximity. Fly to factories, walk lines, negotiate over dinner. If that sounds tedious, you'll hate it. If it sounds like the job, you'll have more autonomy than most VPs.

Location: San Francisco Workplace: OnSite ABOUT HUMAN ARCHIVE Human Archive is a research lab focused on modeling human embodied intelligence. Humans are the most sophisticated biological systems we have ever observed, yet we still do not fully understand ourselves. Research into human physical intelligence — including the human hand, proprioception, and vision — remains largely unsolved. Our mission is to recover human embodied intelligence as a learned model. To achieve this, we build custom hardware products, deploy them globally at scale, and publish research. Today, our data is used for robotics and world modeling, but the broader opportunity is advancing scientific research into intelligence itself. Founded by Stanford and UC Berkeley researchers, we are lean, deeply 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. We are building the infrastructure to accelerate that transition by assembling the Human Archive mafia. 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 help reshape physical labor and work on problems that matter at civilizational scale, join us. THE OPPORTUNITY As a Machine Learning Engineer, you’ll work on multimodal perception, VLA training, robotics post-training, and downstream policy evaluation. This is a hands-on role at the intersection of applied machine learning, data infrastructure, and robotics, where your work directly shapes how data is collected, validated, annotated, and evaluated. You’ll help close the loop between research and data collection by fine-tuning VLAs on downstream policy performance and building post-training and reinforcement learning systems around real-world robotics tasks. You’ll be expected to make architectural decisions, own projects end-to-end, and operate in highly ambiguous research environments given the novelty and scale of our multimodal datasets. Your work will help shape how frontier labs and leading robotics companies train their models, transforming physical labor markets and economies while contributing to broader research into human embodied intelligence. WHAT YOU’LL DO - Build systems for multimodal perception, annotation, dataset QA, and robotics evaluation - Publish research on multimodal data by fine-tuning and evaluating VLA models on downstream robotics tasks and policy performance - Build post-training and reinforcement learning systems around robotics failure modes and corrective demonstrations - Work across video understanding, tracking, pose estimation, temporal modeling, and multimodal alignment - Develop tooling for benchmarking, observability, and temporal efficiency - Prototype quickly, ship rapidly, and iterate from real-world robotics deployments and research feedback WHAT WE’RE LOOKING FOR - Passionate, mission-driven individuals who have demonstrated exceptional ownership in previous work - Engineers who want their work to directly impact the next frontier of physical AGI - Strong ML engineering fundamentals across robotics, computer vision, and perception systems - Experience with video understanding, tracking, pose estimation, robotics, or real-world sensor systems - Strong technical intuition and ability to move quickly in ambiguous research environments - Published research or production experience in robotics, embodied AI, reinforcement learning, motion capture, or vision systems is a strong plus

Location: San Francisco ABOUT HUMAN ARCHIVE Human Archive is a research lab focused on modeling human embodied intelligence. Humans are the most sophisticated biological systems we have ever observed, yet we still do not fully understand ourselves. Research into human physical intelligence — including the human hand, proprioception, and vision — remains largely unsolved. Our mission is to recover human embodied intelligence as a learned model. To achieve this, we build custom hardware products, deploy them globally at scale, and publish research. Today, our data is used for robotics and world modeling, but the broader opportunity is advancing scientific research into intelligence itself. Founded by Stanford and UC Berkeley researchers, we are lean, deeply 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. We are building the infrastructure to accelerate that transition by assembling the Human Archive mafia. 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 help reshape physical labor and work on problems that matter at civilizational scale, join us. About the Role This is a full-stack hardware engineering role spanning mechanical, electrical, firmware, embedded systems, and manufacturing. The engineer in this role will own integration across all layers of the system and drive manufacturing execution in China — from vendor selection through production ramp. You will work directly on wearable sensing systems involving synchronized cameras, motion capture, tactile sensing, embedded compute, and power systems operating under real-world deployment constraints. Mandarin fluency and established relationships in Chinese manufacturing are required. A background in mechatronics, systems engineering, robotics, or embedded hardware is strongly preferred. Open to exceptional new graduates and early-career engineers (2023–2026). What You’ll Do - Lead hardware engineering and manufacturing execution for Human Archive’s multimodal wearable systems - Own integration across power systems, sensor synchronization, embedded compute, thermal systems, and mechanical packaging - Debug failures across electrical, firmware, thermal, RF, and mechanical layers under real-world deployment conditions - Review CAD, schematics, PCB layouts, and embedded firmware behavior and drive corrective action with engineering justification - Prototype, wear-test, deploy, and iterate rapidly on wearable sensing systems used in large-scale global operations - Work directly with stereo depth cameras, IMUs, motion capture systems, tactile hardware, and embedded sensing platforms - Coordinate across hardware, software, operations, and data teams to translate product requirements into manufacturable systems under aggressive timelines What We’re Looking For - Strong background in mechatronics, robotics, systems engineering, embedded systems, or equivalent hands-on experience - Experience building battery-powered electronics, embedded Linux systems, sensor integration systems, or wearable hardware - Ability to debug hardware and embedded systems using serial tools, oscilloscopes, logic analyzers, and low-level debugging workflows - Strong mechanical judgment with the ability to review CAD and identify structural, ergonomic, thermal, or reliability issues - Ability to move quickly in ambiguous, high-ownership environments with aggressive timelines - Strong communication skills and ability to coordinate across engineering, manufacturing, and operations teams - Comfortable operating as both an individual contributor and technical leader in a fast-moving startup environment Strong Plus - Mandarin fluency and active manufacturing relationships in China (Shenzhen, Dongguan, or equivalent ecosystems) - Experience working with motion capture systems, IMUs, stereo depth cameras, tactile sensing, or wearable robotics - Experience bringing hardware products from prototype through mass production deployment - Experience working on robotics, embodied AI, multimodal sensing, or large-scale wearable systems Location Globally deployed. Primary operational presence in China (Shenzhen / Dongguan) and San Francisco.