42dot
42dot
42dot — автомобиль технологиялары мен логистика тоғысындағы мобильділікке арналған жасанды интеллект компаниясы. Оның жұмысы бағдарламалық жасақтамамен анықталатын көлік технологияларына, автономды электр көліктеріне және ауқымды қалалық тасымалды қамтамасыз ететін бағдарламалық жасақтама мен деректер инфрақұрылымына бағытталған. Компания көлік бағдарламалық жасақтамасын, автопарк деректеріне арналған платформаларды, қабылдау және басқару үдерістеріне арналған жасанды интеллект модельдерін, сондай-ақ автономды қызметтерді іске қосуға арналған TAP! мобильділік операциялық жүйесін әзірлейді. Көлік электроникасы мен бағдарламалық жасақтамаға негізделген архитектуралар бойынша зерттеулер мен ынтымақтастық арқылы 42dot мобильділік жүйелерін анағұрлым автономды, бейімделгіш және басқаруға ыңғайлы етуді мақсат етеді.

Deep Learning Engineer, Text-to-Speech Development

Optimize text-to-speech models for Gleo AI’s in-vehicle voice experiences. Build real-time, multilingual speech synthesis for on-device and server environments.

Сипаттама

  • Optimize TTS models for on-device and server environments
  • Port and optimize models for NPU and other AI accelerator environments
  • Reduce model size and improve performance through quantization
  • Develop real-time streaming speech synthesis systems and optimize latency
  • Develop and deploy multilingual, multi-speaker TTS models
  • Research and develop advanced TTS models based on LLMs and flow matching
  • Build speech synthesis datasets with generative models and improve data quality
  • Analyze and resolve TTS model and service issues in production environments
  • Integrate researched and developed TTS technologies into vehicle products and services

Талаптар

  • At least 3 years of relevant TTS experience
  • Foundational knowledge of speech synthesis and TTS concepts
  • Experience with model compression and computational optimization
  • Experience optimizing quantization, memory usage, and latency
  • Experience porting and optimizing models for NPU and other AI accelerator environments
  • Experience optimizing models with TensorRT and ONNX
  • Understanding of audio signal processing
  • Development and debugging experience in Linux environments
  • Programming proficiency in Python, C++, or shell
  • Proficiency with open-source deep learning frameworks such as PyTorch
  • Experience developing multilingual and multi-speaker TTS models is preferred
  • Research or development experience with speech or audio tokenization technologies is preferred
  • Publication as an author in a leading conference or journal in speech synthesis, machine learning, or artificial intelligence is preferred
  • A relevant master's or doctoral degree, or completion of such a program, is preferred
  • Korean proficiency information must be provided

Артықшылықтар

  • Applicants eligible for national merit or employment protection are preferred
  • Applicants with a registered disability certificate are preferred
  • A three-month probationary period may apply
  • A reference check may be conducted with the applicant’s consent after the interview process is complete

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