Camera Systems and Calibration Engineer

About Human Archive

• Human Archive is a research lab backed by Y Combinator 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.

• What you'll work on
• The single hardest role on the team. You'll own the entire optics and calibration stack — lens selection, image quality, intrinsics, extrinsics, ISP tuning, multi-camera alignment. End to end.

Optics and sensor selection

Lens characterization (MTF, distortion, chromatic aberration)

Sensor variant evaluation and selection

Optical mount tolerance budget with the mechanical team

IR filter and lens shading correction approach

Image quality and ISP tuning

AE, AWB, color matrix, gamma, lens shading correction

Multi-camera color and exposure consistency

Image quality validation in mixed real-world lighting

Multi-stage calibration pipeline

Camera intrinsics and fisheye distortion modeling

Stereo and multi-camera extrinsics

Camera-IMU spatial and temporal calibration

Magnetometer calibration in the assembled stack

Calibration infrastructure

Rig design and fixture builds (turntables, lighting, targets)

Calibration software pipeline

Automated verification and QA systems

Documentation for factory deployment

Production and field calibration

Factory-floor calibration procedure

Per-unit calibration QA gating

Field calibration drift monitoring

Sensor / lens transition tooling

Required technical experience

Hands-on multi-camera calibration (intrinsics, stereo, multi-rig)

Fisheye distortion modeling (Kannala-Brandt or equivalent)

IMU calibration: bias, alignment, Allan variance, temperature curves

Calibration tooling and infrastructure for production

Comfortable in both the optics lab and the calibration software stack

Strong plus

OpenCV, Kalibr, or similar calibration frameworks

ISP tuning on Qualcomm, NXP, or Ambarella platforms

AR/VR, autonomous vehicle, or research-grade capture device background

Camera-IMU temporal alignment

Manufacturing calibration line experience

Uncertainty quantification and error analysis

About this role Your work determines whether thousands of hours of captured data is usable. Bad calibration is silent — data passes acceptance and fails downstream model training months later. The candidate pool is small. We pay top of band.