---
title: 'Computer Vision Engineer at BrightAI Corporation'
canonical: 'https://feeny.ai/job/computer-vision-engineer-brightai-corporation-palo-alto-g591gyvk3dcm'
type: 'job'
last_seen: '2026-09-13'
---

# Computer Vision Engineer at BrightAI Corporation

- **Company:** BrightAI Corporation
- **Location:** Palo Alto, CA
- **Posted:** 2026-05-20
- **Last confirmed live:** 2026-09-13
- **Apply:** https://job-boards.greenhouse.io/brightai/jobs/6002012004

## Job description

Computer Vision Engineer — Perception for Autonomy

Location: [Palo Alto / hybrid]

The role:

We fly drones that inspect real infrastructure. That means reconstructing sites accurately enough to detect change over time, and giving the autonomy stack a picture of the world it can actually act on.

You'll own perception for a moving platform — reconstruction, pose, and the simulated environments we use to train and evaluate flight behavior. You'll work closely with the autonomy side without owning the flight controller.

What you'll work on:

- Reconstruction — Gaussian splatting and photogrammetric pipelines producing metrically accurate, georeferenced scenes from drone imagery
- Pose and state estimation — bundle adjustment, RTK/GNSS and IMU fusion, visual-inertial odometry, multi-camera calibration
- Simulation for autonomy — turning reconstructions into training and evaluation environments for flight policies, and characterizing where sim diverges from reality
- Change detection across reconstructions separated by weeks or months
- Perception in the loop — defining what reconstruction and detection deliver to planning, and what happens when the estimate degrades
- Detection and auto-labeling models running on the aircraft under real latency and power budgets

What we need:

- 2+ years in computer vision or robotics perception, with systems that ran outside a lab
- Solid multi-view geometry — you can reason about what your estimator is doing and debug a bundle adjustment that won't converge
- Hands-on SLAM, SfM, or visual-inertial odometry
- Strong PyTorch; real experience training and debugging models on field data that doesn't look like the benchmark
- Have worked on a moving platform — drone, vehicle, or robot — where ground truth is expensive and failures happen on site
- Comfortable at the hardware boundary: camera sync, calibration rigs, reading flight logs
- Enough robotics literacy to talk to the autonomy team — you know what a planner needs from perception and why latency and failure modes matter to it
- Writes clearly enough that another team can act on your design doc

Strong signals:

- 3DGS or NeRF, especially large outdoor scenes
- Reconstruction-backed simulation for robot training
- Sim-to-real transfer or learned dynamics
- ROS/ROS2, PX4/ArduPilot exposure
- C++ alongside Python
- Thermal, depth, or lidar fusion

How we work:

Small team, high autonomy, short path from prototype to field trial. Direct access to real aircraft and real customer sites. We hire people who go find the failure themselves.

## About BrightAI Corporation

## Company Overview
- **One-liner**: BrightAI provides a Physical AI platform that makes the invisible state of critical infrastructure visible and actionable, enabling proactive operations.
- **Entity Type**: Private (Series A, $51M raised in July 2025)
- **Headquarters**: Palo Alto, California, United States
- **Founded**: 2019
- **Founders**: Alex Hawkinson, Nathan Hanks

## Core Business
- **Primary Industry**: AI-powered critical infrastructure management
- **Target Customers**: B2B/Enterprise – owners and operators of essential services in water, power, gas compression, pest control, HVAC, and manufacturing
- **Mission/Purpose**: “Beyond human capacity—we take advanced AI and autonomous technology and make the invisible state of physical infrastructure visible and actionable.”

## Products & Services
- **[Stateful Platform](https://bright.ai/)**: An edge AI platform that ingests sensor data and existing operational records to provide continuous monitoring, root-cause diagnosis, automated dispatch instructions, and machine learning. Deployed across physical assets and environments.
- **Workforce Wearables & Copilots**: Real-time AI-powered insights, communication, and operational support for field workers.
- **Asset & Site Visibility**: Real-time monitoring and proactive asset management for long-term system reliability.
- **Autonomous Inspection**: Safe, reliable data collection from remote and hard-to-access sites using robots and drones.

## Market Standing
- **Valuation**: Not publicly disclosed
- **Key Metrics**:
  - **Annual Revenue**: $75M (estimated, per LinkedIn data)
  - **Total Funding**: $66M (Seed $15M in Nov 2024, Series A $51M in July 2025)
  - **Headcount**: 103 employees (+121.7% YoY)
  - **Deployments**: 250K+ Stateful AI endpoints in the field; 50K+ locations in operating environments
- **Notable Investors/Partners**:
  - Series A lead investors: Khosla Ventures, Inspired Capital
  - Partners: Industry leaders in infrastructure (specific names not disclosed)
- **Growth Signals**:
  - Surpassed $100M milestone (likely an operating or revenue metric) in mid-2025
  - Added senior leaders from Microsoft, Evernote, and Intel in June 2025
  - 15 active job openings; monthly job posting growth +114.3%, yearly +650%

## Competitive Advantages
- **Proactive vs. Reactive**: Shifts infrastructure management from emergency repairs to continuous, predictive AI-driven operations.
- **Full-Stack Physical AI**: Combines edge computing, computer vision, LLMs, time-series signal processing, and robotics into one platform.
- **Founder Expertise**: CEO Alex Hawkinson previously founded SmartThings (acquired by Samsung) and co-founded EfficientAI and OurSky.
- **Real-World Scale**: Proven across 50K+ harsh environments (pipelines, power poles, mining vehicles).

## Strategic Focus
- **Scale Edge AI Deployments**: Accelerate adoption of the Stateful Platform across more infrastructure sectors globally.
- **Expand Leadership & Talent**: Strengthen executive team with deep tech and IoT experience to support rapid growth.
- **Deepen Autonomous Capabilities**: Invest in computer vision, LLM/RAG, time-series signal processing, and robotics to further reduce human intervention in inspection and dispatch.

## Why Work Here
- **Culture**: Values “Curious, Relentless, Collaborative, Impactful.” Emphasis on hands-on problem solving, ownership, and leaving a legacy.
- **Work Model**: Distributed team across the US (San Francisco to New York); remote/hybrid policy not explicitly stated but likely flexible given nationwide team.
- **Engineering Environment**: Deep talent pool across AI, embedded systems, cloud, and robotics; engineers work on cutting-edge physical AI problems.
- **Growth Stage**: High-growth company with 121.7% headcount growth YoY and substantial funding, offering career acceleration.

## Sources
1. [BrightAI Homepage](https://bright.ai/)
2. [BrightAI About Us](https://bright.ai/about-us/)
3. [BrightAI Careers Page](https://bright.ai/careers/)
4. [BrightAI Job Board (Greenhouse)](http://job-boards.greenhouse.io/brightai)
5. [BrightAI LinkedIn Company Page](https://www.linkedin.com/company/brightai)

## Other roles at BrightAI Corporation

- [Senior AI Engineer (Edge Dialog Systems)](https://feeny.ai/job/senior-ai-engineer-edge-dialog-systems-brightai-corporation-palo-alto-bhqr0tbw9qgq) — Palo Alto, CA
- [Senior / Staff Engineer, Robotics](https://feeny.ai/job/senior-staff-engineer-robotics-brightai-corporation-palo-alto-6w2yd82qetnf) — Palo Alto, CA
- [Staff Product Manager](https://feeny.ai/job/staff-product-manager-brightai-corporation-palo-alto-skvg6872kq3x) — Palo Alto, CA
- [AI Engineer, Time-Series Signal Processing](https://feeny.ai/job/ai-engineer-time-series-signal-processing-brightai-corporation-palo-alto-w5rdhqg2t6sd) — Palo Alto, CA
- [Senior AI Engineer – LLM, RAG](https://feeny.ai/job/senior-ai-engineer-llm-rag-brightai-corporation-palo-alto-10vr74j6k2b3) — Palo Alto, CA
- [Computer Vision Engineer](https://feeny.ai/job/computer-vision-engineer-observable-space-los-angeles-qr57v89sp431) — Los Angeles, CA
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