Lead Camera Engineer

Sabi•San Francisco, CA

About The Position

We're a small team solving one of the hardest problems in human-computer interaction: a noninvasive wearable that turns thought into text, no surgery required. By pairing ultra-high-density neural sensing with our Brain Foundation Model, we decode neural signals with a fidelity once reserved for implants. Our mission is to give a billion people a direct link between mind and machine - expanding how humans think, communicate, and create. We are building a next-generation AI companion wearable powered by EEG/BCI technology. Our device reads and responds to neural signals in real time, creating a deeply personal experience that adapts to each user. This is not another productivity tool or a gadget — it is a new category of technology built around human potential. We are backed by strong investors, moving fast, and assembling a world-class team to bring this to market. If you thrive at the frontier of what’s possible and want to build something that genuinely changes how people interact with their own minds, we want to talk to you. You will own the full camera system of our wearable — from sensor selection and optical design, through image processing and compression, to multi-camera capture, and streaming. Our first device carries multiple image sensors arranged around the head to deliver near-360° spatial coverage on a constrained MCU using a multiplexed capture architecture, with a clear path to a more capable image-processing pipeline and higher-end sensors as we scale. You will report to the Head of Hardware, with regular exposure to Sabi’s CEO and CTO, and partner closely with the EE, FW, product design, and reliability leads. You will also work extensively with external engineering teams at our camera module suppliers and contract manufacturers — the work is outsourced; the accountability is yours.

Requirements

10+ years of camera engineering, with at least one shipped consumer product (smartphone, wearable, action camera, AR/VR, or comparable) where you owned the camera subsystem.
Deep expertise in image sensor architectures, sensor interfaces (parallel and high-speed serial), and image-processing pipelines.
Demonstrated optical design experience for compact consumer products — lens selection, FOV tuning, optical stack, AR coating.
Hands-on experience characterizing and tuning image quality (exposure, white balance, color, low-light, dynamic range) using structured test environments.
Direct experience driving camera component selection and benchmarking with second-source planning.
Experience working with overseas camera module suppliers and driving DfM, calibration, and quality at volume.

Nice To Haves

Deploying CV models or vision pipelines on dedicated low-power AI accelerators.
Multi-camera systems — calibration, synchronization, stitching, panoramic, or stereo.
Low-power image sensors for battery-constrained products.
Computer-vision background — VSLAM, scene understanding, on-device inference.
Experience navigating the social and privacy considerations of body-worn cameras.

Responsibilities

Own the camera system end-to-end — sensor selection, optical design, capture pipeline, image processing, multi-camera architecture, calibration, image quality.
Drive part selection and benchmarking across the camera system — image sensors, lens stacks, module suppliers — with second-source planning.
Drive the optical design — lens FOV and stack-up, AR coating, hyperfocal tuning, and validation across head pitches and body coupling.
Specify the electrical and mechanical interfaces cameras need from the rest of the system, and partner with the EE lead on layout, the FW lead on capture drivers, and the product design lead on pod integration.
Validate combined field-of-view, blind spots, and seam overlap, and define the calibration and stitching path for future panoramic and CV use cases.
Set the image-quality bar — exposure, white balance, low-light, dynamic range, motion handling — and the test methodology that holds it as we scale.
Partner with the reliability lead on component-level reliability for the camera system — image sensor lifetime, lens and AR-coating durability, optical-stack robustness.
Ship the product by the end of year, and help build and grow the camera team.