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Human Archive

Provides real-world multimodal data for robotics

Field Operations

Operations & LogisticsConfirmed live in the last 24 hours
Full-timeIndiaNo salary listedIn-person

About the Job

Requirements

  • The role targets someone early in their career with 1–5 years of experience, or an exceptional dropout.
  • 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.
  • Resilience, resourcefulness, and comfort solving difficult operational problems.
  • Prior experience in operations, logistics, consulting, marketplaces, field work, or startups is a plus.

Responsibilities

  • Source 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.

Desired Qualifications

  • Prior experience in operations, logistics, consulting, marketplaces, field work, or startups.

About the Company

Human Archive

Provides real-world multimodal data for robotics

Human Archive collects and curates real-world, multimodal data to train physical AI and robotics systems. It uses a hardware-enabled platform with camera-equipped headsets, tactile gloves, and motion-capture systems to record and synchronize egocentric video, depth, audio, motion, and haptic logs across homes, restaurants, and industrial settings. The data undergoes quality assurance, anonymization, and annotation to produce high-fidelity datasets for robotics companies and AI research labs. By providing large-scale data collection and labeling infrastructure through its partner network, the company aims to address the shortage of real-world training data for embodied intelligence and physical AI models.

Company size
51-200
Company stage
Seed
Total funding
$8.3M
Headquarters
San Francisco, CA
Founded
2025

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