---
title: 'Operations Manager (on-site) at Human Archive'
canonical: 'https://feeny.ai/job/operations-manager-on-site-human-archive-india-89the0bwz925'
type: 'job'
last_seen: '2026-09-09'
---

# Operations Manager (on-site) at Human Archive

- **Company:** Human Archive
- **Location:** India
- **Employment:** full-time
- **Posted:** 2026-08-13
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.ashbyhq.com/humanarchive/9843105d-f7c0-4e5e-ad6e-999836e61fc5

## Job description

## ABOUT HUMAN ARCHIVE

Human Archive is a data lab modeling human embodied intelligence.

We're researchers from Stanford, Berkeley, NYU GRAIL, UPenn GRASP, JHU Robotics and national robotics champions, backed by Y Combinator and $8.2M.

Hardware — We design, manufacture and calibrate thousands of custom collection rigs, gloves and wrist cameras, with our hardware team in Shenzhen.

Operations — We have 100+ full-time team members collecting large-scale multimodal video and sensor data from 100,000+ contributors and 500+ industry partners across homes, hotels, restaurants, agriculture, manufacturing, construction and retail in 30+ countries. In India, our operations are headquartered in Bengaluru and run live across Delhi NCR, Bengaluru, Mumbai, Goa etc.

Software — We develop custom 3D perception and annotation models tailored to our hardware, and train robot policies on our datasets. Our SLAM and hand-pose models achieve state-of-the-art performance.

Despite decades of research, we still barely understand how humans think, move or interact with the world. Human Archive's datasets are foundational infrastructure for automating manual labor, increasing global abundance and advancing our understanding of the brain.

## ABOUT THE ROLE

As an Operations Manager, you own the deployment. From the moment equipment leaves our storage point to the moment the day's data is verified, it is yours to run — a team of five to six operators, a live site, and a set of problems nobody can solve for you from a desk.

The stakes are real. Robots learn from what we capture. A deployment run well produces data that trains machines to work with their hands; a deployment run badly produces footage nobody can use. That call gets made on the floor, by you, in the moment.

It suits someone who is equally comfortable talking to a mechanic mid-shift and holding a strict data protocol when a site is pushing back. Most people can do one. We are looking for the ones who can do both.

## A DAY ON DEPLOYMENT

Reporting time varies by deployment and can be early morning. A typical day runs as follows.

- Start of day — Reach the storage point, for example our Gurgaon dark store. Collect and verify camera units, batteries, memory cards and accessories against the assigned inventory on the app.
- Travel — Move to the deployment site with your team.
- On arrival — Meet the site point of contact. Walk the floor and confirm the day's capture plan, including which workers and stations are being recorded.
- Briefing — Brief your five to six operators. Assign stations, fit camera systems on the workers, run a test capture.
- Collection — Run the day's capture. Move between stations checking framing, battery levels and storage. Handle what goes wrong: a worker steps away, a shift changes, a station becomes inaccessible. You make the call on the spot.
- Wrap — Close capture and complete the taxonomy for everything collected on task level.
- Day end — Return to the storage point, reconcile inventory with the dark store manager, flag damaged units, transfer data and submit the deployment report.

## RESPONSIBILITIES

- Collect and verify camera inventory, batteries and accessories from the local storage point each morning
- Travel with your team to the deployment site and set up for the day's collection
- Brief and manage five to six field operators through the collection plan
- Meet and coordinate with the site point of contact, typically a Director, Operations Head or owner of a factory, resort or restaurant
- Check data quality through the day, including camera framing, battery levels and storage
- Complete and verify the taxonomy for all footage collected on site
- Reconcile inventory at day end and return it to the dark store manager
- Transfer and upload the day's data, and submit the deployment report

## WHO WE'RE LOOKING FOR

Non-negotiable

- Strong spoken English and Hindi. You are often our first point of contact with Directors, Operations Heads and owners of factories, resorts and restaurants.
- Willingness to work on site and travel, not from a desk
- Ability to give clear direction to field teams in Hindi and English
- Ability to make decisions independently when a deployment does not go to plan

We're hiring two kinds of people

1. Freshers: 2025 and 2026 pass-outs

Startup internship experience strongly preferred. If you have interned at an early-stage company and know what it is like when the process does not exist yet and you have to build it, this role will make sense to you.

1. People with 1–3 years of field or operations experience

Prior experience as an Operations Manager, City Ops, Fleet Ops or Field Ops at a startup. Quick commerce, home services, hyperlocal delivery and on-demand backgrounds map directly onto this role — companies like Snabbit, Blinkit, Zepto, Swiggy, Urban Company, Rapido and Porter.

Prior experience is useful but not required. We train on our protocol and taxonomy. What we cannot train is spoken English and ownership.

## THIS ROLE IS NOT FOR YOU IF

- You want a fixed desk and a fixed city
- You want predictable 10-to-6 hours
- You are uncomfortable spending your day on factory floors, in kitchens and on shop floors
- You would rather escalate a problem than solve it on the spot

## TRAVEL

This role requires substantial travel. A typical month may include a week in Delhi NCR, a week in Bengaluru and a week in Assam. You should be comfortable with this before applying.

- Base location is Delhi NCR.
- All outstation work-related travel, accommodation, meals and commute are paid by the company and are not part of your CTC.

## WORKING SCHEDULE

- 6-day work week
- Actual working hours are approximately 9 to 10 hours. On deployment days a significant part of the day is spent travelling, over and above working hours.
- Reporting time depends on the deployment and can be early morning.
- Sunday deployments are limited to a maximum of two per month.
- On non-deployment days you handle data transfer and upload, deployment planning, reporting and site coordination. These days run on more regular hours.

## ELIGIBILITY

- Any graduate degree (BBA, BA, B.Com http://B.Com, BHM, B.Tech http://B.Tech or equivalent). Hospitality, hotel management and general management backgrounds do particularly well in this role.
- Batch: 2025 and 2026 pass-outs, or up to 3 years of relevant experience
- No minimum CGPA cutoff. We hire on the interview, not the marksheet.

## COMPENSATION

- Total CTC: ₹4.2–7 LPA, based on interview performance
- 100% fixed. There is no variable or performance-linked component.
- Probation: 2 months at full salary. No deduction during probation.
- No service bond or training bond of any kind.

## REPORTING AND GROWTH

You report to the Zone Head and the Operations Head, and work directly with the founding team. Each Operations Manager runs one deployment team of five to six field operators, with a home city and rotation across active national sites.

Typical progression for strong performers:

- Regional Manager — around 8 months. Owns multiple deployment teams across a zone.
- City Head — around 18 months. Owns a city's full operations, including site partnerships and vendor relationships.

We expect our operations leadership to come from this cohort.

## About Human Archive

## Core Business
- **Primary industry**: Data infrastructure for robotics and embodied artificial intelligence
- **Target customers**: Frontier AI labs, robotics companies, and academic researchers (B2B)
- **Mission**: To build the “Common Crawl for human sensorimotor intelligence” – a massive, aligned multimodal dataset that captures how humans interact with the physical world, enabling robots to automate manual labor and advancing understanding of human cognition.

## Products & Services
- **HA-Multi Dataset**: Fully aligned multimodal dataset including RGB-D (stereo depth via IR dot projection), tactile gloves, body IMUs, wrist cameras, and audio. Provides structured outputs such as 3D MANO hand reconstructions, 2D tactile force maps, depth maps per timestamp, and human pose reconstructions.
- **HA-Ego Dataset**: Monocular RGB vision dataset with wrist cameras, annotated with environment/scene descriptions, task labels, hand tracking, object segmentation, SLAM, and 3D pose reconstruction.
- **Custom Hardware Rigs**: Proprietary headset-mounted cameras, tactile gloves, full-body motion capture suits, and wrist cameras designed for synchronized data capture across multiple modalities.
- **Data Collection & Annotation Services**: End-to-end pipeline including QA, anonymization (face blurring), and annotation, delivered as structured datasets to customers.
- **Model Fine‑Tuning & Evaluation**: Internal capability to fine‑tune AI models on collected data and test them on robots to validate dataset quality.

## Market Standing
- **Valuation / Market Cap**: Not disclosed (seed‑stage private company)
- **Key Metric**: Total funding raised – $8.2 million (seed round, announced May 2026)
- **Notable Investors/Partners**: Wing Venture Capital, NVP Capital, Y Combinator, and angels from OpenAI, Nvidia, Google, Mercor, AfterQuery, BAIR, SAIL, Brad Boa, and Meta. [techcrunch.com](https://techcrunch.com/2026/05/26/human-archive-taps-into-indias-services-startups-to-collect-data-for-physical-ai/)
- **Growth Signals**:
  - 1,000+ active headsets deployed across multiple locations (homes, hotels, restaurants, etc.)
  - Capacity to collect up to 8,000 hours of data per day
  - Signed national‑level partnerships to scale contributor network to 50,000+ people
  - Expanding operations from India into Southeast Asia and the United States
  - Already shipped datasets to frontier research teams

## Competitive Advantages
- **First‑mover in synchronized multimodal data at scale**: No other company has been able to simultaneously capture headset RGB‑D, force feedback, full‑body motion capture, and wrist camera data in a time‑aligned manner across thousands of real‑world environments.
- **Custom hardware**: Over seven proprietary hardware products (rigs, caps, tactile gloves, suits) designed specifically for high‑quality, scalable data collection.
- **On‑the‑ground operations in India**: Low‑cost, high‑volume data collection through partnerships with gig‑economy service providers, allowing rapid scaling.
- **Strong founding team**: Researchers from Stanford and Berkeley with deep backgrounds in robotics, hardware, and operations.

## Strategic Focus
- **Scaling data collection**: Expanding the contributor network to 50,000+ people and entering new geographies (Southeast Asia, U.S.).
- **Building the “Common Crawl for human sensorimotor intelligence”**: Creating the largest annotated multimodal dataset of human physical interaction.
- **Vertical integration**: Developing fine‑tuning and model evaluation services to demonstrate dataset quality and capture more value.
- **Partnerships with service companies**: Offering discounted cleaning, cooking, or other services in exchange for data collection consent (early pilot stage).

## Why Work Here
- **Mission‑driven**: Opportunity to work on foundational infrastructure for automating manual labor and advancing embodied AI – a historic inflection point.
- **Early‑stage impact**: Join a Y Combinator‑backed startup just months old, with direct influence on product, data pipeline, and research direction.
- **Work environment**: Hybrid/remote options available; offices in San Francisco (in‑office for some roles, remote for others). [builtin.com](https://builtin.com/company/human-archive)
- **Team culture**: Small, tight‑knit team (18 employees as of mid‑2026) of engineers and operators who “dropped out of Stanford and Berkeley” to pursue this vision.
- **Cutting‑edge tech**: Work with custom hardware, multimodal sensor fusion, large‑scale data pipelines, and state‑of‑the‑art robotics models.
- **Open roles**: Engineering (Research, ML, Infrastructure, Firmware, Embedded, Hardware Test) and Operations (Head of Operations). [ycombinator.com](https://www.ycombinator.com/companies/human-archive/jobs)

## Sources
1. [humanarchive.ai](https://www.humanarchive.ai/) – Company website
2. [builtin.com](https://builtin.com/company/human-archive) – Company profile, headcount, office locations, job listings
3. [ycombinator.com](https://www.ycombinator.com/companies/human-archive) – Y Combinator company page, founding details, funding, jobs
4. [techcrunch.com](https://techcrunch.com/2026/05/26/human-archive-taps-into-indias-services-startups-to-collect-data-for-physical-ai/) – TechCrunch article on $8.2M seed round, business model, and operations

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