---
title: 'Machine Learning Engineer at Human Archive'
canonical: 'https://feeny.ai/job/machine-learning-engineer-human-archive-san-francisco-gwj3j215n9v4'
type: 'job'
last_seen: '2026-09-09'
---

# Machine Learning Engineer at Human Archive

- **Company:** Human Archive
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-05-09
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.ashbyhq.com/humanarchive/98291570-1c51-4517-93f8-845fea602f43

## Job description

## 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

## 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

## Other roles at Human Archive

- [Operations Manager (YC-Backed, High-Growth Startup)](https://feeny.ai/job/operations-manager-yc-backed-high-growth-startup-human-archive-india-9z2awb5n92ft) — India
- [Head of Talent Acquisition](https://feeny.ai/job/head-of-talent-acquisition-human-archive-india-d010qcxhmh8s) — India
- [Chief of Staff](https://feeny.ai/job/chief-of-staff-human-archive-india-06rpdhx25fvz) — India
- [Operations Manager (on-site)](https://feeny.ai/job/operations-manager-on-site-human-archive-india-89the0bwz925) — India
- [Founder's Office Intern - Partnerships](https://feeny.ai/job/founder-s-office-intern-partnerships-human-archive-india-6fzh5878617c) — India
- [Deployment Associate - Field Operations](https://feeny.ai/job/deployment-associate-field-operations-human-archive-india-k919yyjc5q57) — India
- [Operations Manager](https://feeny.ai/job/operations-manager-human-archive-india-dhnzsq0kkv6g) — India
- [Strategy & Project Lead (Data Operations)](https://feeny.ai/job/strategy-project-lead-data-operations-human-archive-india-4wewntj07j0x) — India
- [Founder's Office](https://feeny.ai/job/founder-s-office-human-archive-india-s0hq6npjsmme) — India
- [Dark Store & Inventory Operations Lead](https://feeny.ai/job/dark-store-inventory-operations-lead-human-archive-india-bygzve0g2txa) — India