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Applied Intuition

Builds software for autonomous vehicles

Computer Vision Engineer

Computer VisionUpdated on Nov 9
Full-timeSunnyvale, CA, USA$150k - $225k /yrIn-person

About the Job

Requirements

  • An MS or PhD in Computer Engineering, Robotic Engineering, or Computer Science, or equivalent, or at least 5 years of relevant experience working with simulation, machine learning, and machine-learning infrastructure.
  • At least 5 years of industry experience supporting computer vision capabilities.
  • Proficiency training machine-learning models in PyTorch on multi-machine, multi-GPU systems.
  • Experience optimizing and deploying machine-learning models to edge devices.
  • Strong experience with agentic coding and proven experience with Python and/or C++.
  • Experience using modern AI-powered development tools such as GitHub Copilot and Cursor to accelerate creation of robust, well-tested systems.
  • Ability to work with remote software development, handle and process large datasets, and learn new software and algorithms with little supervision.
  • Must be willing to travel as projects require, usually for software/hardware integration and/or demonstrations; estimated average travel is 2–5 days every other month (10–20%).
  • Must be a U.S. citizen.
  • Must hold or be eligible to obtain and maintain a U.S. security clearance.

Responsibilities

  • Develop perception models that find and classify targets with an error rate below 1/100.
  • Deploy perception models to Jetson Orin+ boards and optimize models for better-than-real-time performance.
  • Build large foundation models for high-accuracy assisted data labeling.
  • Build tooling across the perception stack, including labeling tools and simulation.
  • Collaborate with Applied Intuition self-driving staff.
  • Scale datasets using state-of-the-art data-generation techniques, including simulation, diffusion, and generative AI.
  • Create and maintain highly optimized models and inference software that provide model results at the maximum attainable frames per second on Jetson-like hardware.
  • Collaborate with hardware, sensor, tracking, autonomy, and testing teams to ensure seamless deployment in on-site DoD testing and demonstration events.

Desired Qualifications

  • A PhD in Computer Vision, Machine Learning, or a related field, with strong academic contributions.
  • A background in generating datasets using simulation engines such as Unreal Engine, NVIDIA Omniverse, and Blender, or 3D asset-creation tools.
  • Experience deeply optimizing transformer-based models for edge devices such as NVIDIA Jetson boards.
  • Familiarity with Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL), including integration and testing on common commercial off-the-shelf hardware devices such as NVIDIA Jetson and Raspberry Pi 5.

About the Company

Applied Intuition

Builds software for autonomous vehicles

Applied Intuition builds software for automakers and operators developing autonomous vehicles and other machines, from passenger cars to industrial equipment. Its Tools for Vehicle Intelligence let engineers test driving behavior in simulated worlds, while Vehicle OS connects software inside a machine with development tools off the vehicle. The Self-Driving System supports driver assistance and fully driverless operation for passenger and commercial vehicles. It sells these systems to businesses and works alongside their engineers to integrate, validate and update vehicle software. Applied Intuition was founded in 2017 and is headquartered in Sunnyvale, California.

Company size
1,001-5,000
Company stage
Series F
Total funding
$1.2B
Headquarters
Sunnyvale, CA
Founded
2017

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