Chief of Staff
Human Archive
Chief of Staff
Human Archive
Provides real-world multimodal data for robotics
Human Archive (YC W26) is hiring someone to lead our end-to-end data annotation operations.
You will work directly with the founder to build and manage a high-performing annotator workforce for robotics data. Your job is to ensure we consistently have the right people, quality, and throughput across multiple projects running simultaneously.
This is a highly hands-on role for someone who is excellent with people, metrics, and fast-moving operations.
Recruit, evaluate, and manage high-quality data annotators
Maintain a high bar for annotation quality and workforce performance
Allocate annotators across multiple simultaneous projects
Track daily throughput, quality, attendance, utilisation, and project targets
Build dashboards and operating systems with our engineering team
Identify bottlenecks and improve annotation workflows
Design incentives that help teams consistently meet daily targets
Forecast staffing requirements for upcoming projects
Manage team leads and resolve day-to-day operational issues
Build processes that can scale from hundreds to thousands of annotators
Extremely good with people and frontline teams
Strong analytical ability and comfort with metrics and dashboards
Excellent at prioritisation and resource allocation
Highly organised and able to manage multiple projects at once
Creative about incentives, hiring, performance, and operations
Clear, direct, and fast communicator
High ownership, energy, urgency, and agency
Comfortable working in a demanding, fast-changing startup environment
Experience at companies such as Surge AI, Scale AI, Mercor, Turing, Outlier, Remotasks, or similar workforce and data-operations businesses is a strong advantage.
On-site in Bangalore.
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.
Explore more opportunities at Human Archive