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
This role is ideal for someone early in their career (1–5 years of experience, or an exceptional dropout) who wants real operational ownership, not a rotational apprenticeship. You’ll work closely with the co-founders and Head of Operations in a high-trust role at the center of execution at Human Archive.
As a Founding Operations Manager, you will own the end-to-end lifecycle of field operations globally, including sourcing and structuring partnerships to unlock access to real-world labor environments, deploying and supporting field teams, and ensuring clean data offload, audit, and closure. Your mandate is to turn site access into reliable, repeatable, high-velocity data collection, even in messy, real-world conditions.
You will build and run core operating systems: coordinating site readiness, managing kits and logistics, leading large field teams during on-site execution, and enforcing post-site workflows that guarantee data quality and operational closure. This is a hands-on execution role: you’ll plan, but you’ll also be on the ground supporting field teams, unblocking hardware and deployment issues, tightening processes, and making sure things actually get done.
What You’ll DoSource and manage deployment partnerships globally
Own field operations from site readiness through post-site closure
Lead field teams and ensure reliable execution during deployments
Run high-velocity data collection campaigns under real-world constraints
Work directly with sensing hardware, deployment kits, upload systems, and offloading workflows
Troubleshoot hardware, deployment, and operational issues in the field
Improve operational systems across deployments, audits, inventory, and payouts
Work closely with hardware, software, and operations teams during deployments
Strong execution ability and willingness to take ownership in fast-moving environments
Ability to manage deployments and field teams under real-world constraints
Strong technical intuition and comfort working directly with hardware and operational tooling
Strong communication skills and ability to make decisions quickly with limited information
Highly resilient, resourceful, and comfortable solving difficult operational problems
Prior experience in operations, logistics, consulting, marketplaces, field work, or startups is a plus
Skills Required
- Strong execution ability in fast-moving environments
- Ability to manage deployments under real-world constraints
- Strong technical intuition and comfort with hardware
- Strong communication skills
- Highly resilient and resourceful
- Prior experience in operations or logistics is a plus
What We Do
Human Archive is a data infrastructure company that collects, labels, and synchronizes multimodal data (video, sensor, audio) to create datasets for training embodied AI and robotics systems. Founded by researchers from Stanford and Berkeley, the company aims to advance robotics foundation models by capturing real-world physical data, helping to automate manual labor and improve understanding of human cognition and spatial computing.









