{"id":450245,"url":"https://alion.io/job/human-archive-camera-systems-and-calibration-engineer","title":"Camera Systems and Calibration Engineer","company":{"id":173852,"name":"Human Archive","domain":"humanarchive.ai","url":"https://alion.io/company/human-archive","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"C","score":60,"open_postings":21,"ghost_share":0.667,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-08T05:47:12Z"}},"role":"Industrial Engineering","role_family":"Industrial Engineering","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Embodied AI","optional":false},{"name":"OpenCV","optional":true}],"status":"live","first_seen_at":"2026-05-25T09:42:45Z","employer_posted_date":"2026-05-25","last_verified_at":"2026-11-08T13:55:39Z","board_verified":true,"closed_at":null,"days_open":167,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":166},"description":"About Human Archive\nHuman Archive is a research lab backed by Y Combinator focused on modeling human embodied intelligence.\nHumans 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.\nFounded 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.\nThe 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.\nWe 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.\nWhat you'll work on\nThe 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.\nOptics and sensor selection\nLens characterization (MTF, distortion, chromatic aberration)\n\nSensor variant evaluation and selection\n\nOptical mount tolerance budget with the mechanical team\n\nIR filter and lens shading correction approach\n\nImage quality and ISP tuning\nAE, AWB, color matrix, gamma, lens shading correction\n\nMulti-camera color and exposure consistency\n\nImage quality validation in mixed real-world lighting\n\nMulti-stage calibration pipeline\nCamera intrinsics and fisheye distortion modeling\n\nStereo and multi-camera extrinsics\n\nCamera-IMU spatial and temporal calibration\n\nMagnetometer calibration in the assembled stack\n\nCalibration infrastructure\nRig design and fixture builds (turntables, lighting, targets)\n\nCalibration software pipeline\n\nAutomated verification and QA systems\n\nDocumentation for factory deployment\n\nProduction and field calibration\nFactory-floor calibration procedure\n\nPer-unit calibration QA gating\n\nField calibration drift monitoring\n\nSensor / lens transition tooling\n\nRequired technical experience\nHands-on multi-camera calibration (intrinsics, stereo, multi-rig)\n\nFisheye distortion modeling (Kannala-Brandt or equivalent)\n\nIMU calibration: bias, alignment, Allan variance, temperature curves\n\nCalibration tooling and infrastructure for production\n\nComfortable in both the optics lab and the calibration software stack\n\nStrong plus\nOpenCV, Kalibr, or similar calibration frameworks\n\nISP tuning on Qualcomm, NXP, or Ambarella platforms\n\nAR/VR, autonomous vehicle, or research-grade capture device background\n\nCamera-IMU temporal alignment\n\nManufacturing calibration line experience\n\nUncertainty quantification and error analysis\n\nAbout 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. 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