Senior Software Engineer, Perceptual Calibration

San Jose, CAfull timeOn Site

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senior

$210k–$290k

H1B: no

Rivet The Senior Software Engineer, Perceptual Calibration owns perceptual calibration for AR wearables and devices, developing algorithms and processes from lab to factory production. This role collaborates with hardware, robotics, perception, and manufacturing teams to ensure accurate and efficient calibration at scale.

Responsibilities

Build computer vision and signal processing algorithms that calibrate the geometric intrinsics, extrinsics, and time offsets of cameras, IMUs, and XR displays.
Develop perceptual calibration processes for Rivet’s range of wearables and devices, covering calibration station design (sensor and target selection, metrology hardware requirements) and controlled data capture conditions.
Deploy data capture processes and calibration binaries to factory sites, working with contract manufacturers (CMs) through bring-up, ramp, and mass production.
Set factory calibration limits using Gage Repeatability & Reproducibility (GR&R) studies and Design of Experiments (DOE), and establish failure analysis processes backed by automated and agentic diagnosis and documented runbooks.
Reduce calibration cycle time through software profiling and refinement, additional or alternative station hardware, and process pipelining.
Develop tooling, visualization, and debugging workflows for end-to-end validation of perceptual calibration, including lab verification of factory calibration results.
Partner with hardware, mechanical, optical, and electrical engineering, robotics, perception, and manufacturing teams to set calibration requirements, design-for-calibration tolerances, and station specifications, and to deliver calibrated products end-to-end.

Qualification

Ability to partner across hardwareExperience with SLAMExperience building wearable

Required

Proven hands-on experience shipping camera, IMU, and/or display calibration solutions into production devices, from lab prototype through factory ramp.
Demonstrated hands-on ability to debug calibration failures, with a deep understanding of both the front-end perception (target detection, feature extraction, data association) and back-end optimization (sensor models, nonlinear least squares, observability) components of geometric calibration pipelines.
PhD + at least 3 years (or MS + at least 7 years) of relevant professional experience.
Experience with robot arms or motion stages for calibration data capture.
Strong background in multi-view geometry, camera and IMU sensor models, coordinate frames, nonlinear optimization, and statistics.
Proficient in C++ or Rust for performance-critical code, and in Python for analysis, automation, and tooling.
Experience developing on Android or embedded Linux devices.
Strong understanding of performance optimization, profiling, synchronization, and CPU/GPU/memory tradeoffs.
Ability to partner across hardware, mechanical, robotics, perception, and manufacturing teams, and with contract manufacturers.

Preferred

Experience with SLAM, visual-inertial odometry (VIO), or online calibration.
Experience calibrating XR displays (distortion, binocular alignment, display-to-camera extrinsics).
Experience building wearable, robotics, aerospace, defense, or embedded perception systems.
Working knowledge of manufacturing test statistics (GR&R, DOE, SPC, Cpk) and high-volume factory bring-up.