Machine Learning Engineer (Voice AI) - Edge & Embedded Systems

silkwise • Japan
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AI Summary

An AI-focused technology company in Tokyo is hiring a Machine Learning Engineer to build reliable voice-related AI features for real-world environments. The role involves developing and improving ML pipelines, optimizing models for edge devices and embedded systems, and implementing modern deep learning approaches. The ideal candidate will have strong skills in Python, C++, and Transformer-based models, with experience in Docker and containerized environments.

Key Highlights
Focus on building reliable voice-related AI features for real-world environments
Optimize models for edge devices and embedded systems
International engineering team with English-speaking workplace and hybrid work style
Key Responsibilities
Develop and improve ML pipelines
Optimize models for edge devices and embedded systems
Implement and test modern deep learning approaches
Build maintainable backend systems using Python and C++
Technical Skills Required
Python C++ Transformer-based deep learning models Docker
Benefits & Perks
Remote work flexibility
Flexible daily schedule
Long holiday allowance
Housing and relocation support
Learning budget and technical training
Team offsites and internal workshops

Job Description


About the Role


An AI-focused technology company in Tokyo is hiring a Machine Learning Engineer. The role focuses on building reliable voice-related AI features for real-world environments.


Responsibilities

  • Develop and improve ML pipelines
  • Optimize models for edge devices and embedded systems
  • Implement and test modern deep learning approaches
  • Build maintainable backend systems using Python and C++


Tech Stack

  • Python, C++
  • Transformer-based deep learning models
  • Docker / containerized environments


Work Environment

  • International engineering team
  • English-speaking workplace
  • Hybrid work style with flexible hours
  • Engineering-driven culture with strong technical collaboration


Perks & Benefits

  • Remote work flexibility
  • Flexible daily schedule
  • Long holiday allowance
  • Housing and relocation support
  • Learning budget and technical training
  • Team offsites and internal workshops


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