Camera Systems and Calibration Engineer

About Human ArchiveHuman 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 onThe 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 selectionLens characterization (MTF, distortion, chromatic aberration)Sensor variant evaluation and selectionOptical mount tolerance budget with the mechanical teamIR filter and lens shading correction approachImage quality and ISP tuningAE, AWB, color matrix, gamma, lens shading correctionMulti-camera color and exposure consistencyImage quality validation in mixed real-world lightingMulti-stage calibration pipelineCamera intrinsics and fisheye distortion modelingStereo and multi-camera extrinsicsCamera-IMU spatial and temporal calibrationMagnetometer calibration in the assembled stackCalibration infrastructureRig design and fixture builds (turntables, lighting, targets)Calibration software pipelineAutomated verification and QA systemsDocumentation for factory deploymentProduction and field calibrationFactory-floor calibration procedurePer-unit calibration QA gatingField calibration drift monitoringSensor / lens transition toolingRequired technical experienceHands-on multi-camera calibration (intrinsics, stereo, multi-rig)Fisheye distortion modeling (Kannala-Brandt or equivalent)IMU calibration: bias, alignment, Allan variance, temperature curvesCalibration tooling and infrastructure for productionComfortable in both the optics lab and the calibration software stackStrong plusOpenCV, Kalibr, or similar calibration frameworksISP tuning on Qualcomm, NXP, or Ambarella platformsAR/VR, autonomous vehicle, or research-grade capture device backgroundCamera-IMU temporal alignmentManufacturing calibration line experienceUncertainty quantification and error analysisAbout 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.