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42dot

Unified platform for multi-modal urban mobility

Edge AI Software Engineer - Autonomous Driving

Embedded EngineeringConfirmed live in the last 24 hours
Full-timeGyeonggi-do, South KoreaNo salary listedHybrid

About the Job

Requirements

  • At least 5 years of development experience in embedded software, AI software, computer vision, or a related field.
  • A master's degree or higher in software engineering, computer vision, artificial intelligence, machine learning/deep learning, or a related field, or equivalent practical experience.
  • Understanding of machine-learning and deep-learning model structures and inference processes.
  • Understanding of CPU, GPU, and NPU hardware architectures, with experience in low-level performance optimization.
  • Proficiency in software development using C/C++, Shell, and Python.
  • Experience developing software based on Linux or QNX.
  • Ability to analyze and optimize software performance in embedded-system environments.

Responsibilities

  • Develop software and optimize execution environments so AI models can perform inference efficiently on hardware accelerators such as GPUs and NPUs.
  • Implement encoding and preprocessing for AI model input signals, such as images, and decoding and postprocessing for model output signals.
  • Profile the performance of AI models and applications in embedded-system environments, and optimize hardware-resource utilization and inference performance.
  • Improve applications and related software frameworks to support continuous updates and deployment of AI models.
  • Participate in developing a performance-validation framework to analyze and predict AI model performance in vehicles in advance.

Desired Qualifications

  • Experience analyzing and optimizing the performance of machine-learning and deep-learning workloads.
  • Experience optimizing and analyzing the performance of linear algebra routines used in deep-learning computation.
  • Experience with system-level optimization of image processing, computer vision, or robotics algorithms.
  • Experience with hardware acceleration and computational optimization using CUDA, MKL, SIMD, or NEON.
  • Experience building inference environments for in-vehicle AI models or developing embedded AI applications.
  • Experience applying VLA or end-to-end autonomous-driving AI models in vehicles and validating their performance.

About the Company

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42dot

Unified platform for multi-modal urban mobility

42dot.ai provides a platform called UMOS (Urban Mobility Operating System) that connects and manages multiple transportation modes—such as cars and drones—within a single system for cities, agencies, and private clients. UMOS enables efficient transportation management, demand-response services, and smart logistics by integrating data and operations across modes, powering operations through a subscription-based platform-as-a-service model. Unlike single-mode solutions, 42dot.ai offers multi-modal, city-focused orchestration that bridges public, private, and logistics needs. The company aims to transform urban mobility by helping cities run more efficiently, cut costs, and improve the experience for commuters and logistics providers.

Company size
501-1,000
Company stage
Growth Equity (Venture Capital)
Total funding
$731.9M
Headquarters
Seoul, South Korea
Founded
2019

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