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42dot

Unified platform for multi-modal urban mobility

Deep Learning Engineer - wake word detection

Natural Language Processing & LLMsUpdated on Nov 10
Full-timePangyo-ro, Bundang-gu, Seongnam-si, Gyeonggi-do, South KoreaNo salary listedHybrid

About the Job

Requirements

  • At least 2 years of relevant experience, or a master's degree as a new graduate applicant.
  • Knowledge of fundamental concepts in speech signal processing.
  • Research experience in modern machine learning or artificial intelligence in speech-to-text or wake-word detection.
  • Ability to develop applications for on-device (edge) devices, including Linux and Android.
  • Programming ability to propose original technologies and solve problems, using C, C++, Python, shell, or similar languages.
  • Ability to use open-source deep learning frameworks such as PyTorch, TensorFlow, Keras, or Caffe.

Responsibilities

  • Design speech-to-text acoustic and language models and build speech databases.
  • Design wake-word detection models and build speech databases.
  • Develop batch and streaming speech applications for server and on-device environments, including Linux and Android.
  • Develop and optimize hardware-efficient models.

Desired Qualifications

  • Experience understanding and using version control systems such as Git.
  • Basic understanding of unit testing, static analysis, test automation, and continuous integration and continuous delivery.
  • Experience developing speech-to-text technology that has been commercialized or deployed as a service.
  • Research experience in speech-to-text based on self-supervised learning or attention-based encoder-decoder methods.
  • Research experience in multilingual speech-to-text.
  • Research experience related to language models for speech recognition.
  • Authorship of papers in leading journals or conferences in speech recognition, machine learning, or artificial intelligence.
  • A master's or doctoral degree, or completion of graduate studies, in a related field.

About the Company

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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