Machine Learning Engineer - Speech AI

In this role, you will join an AI and Robotics team to develop and add new AI-enabled features to a mobile AI communication robot. The team focuses on improving service efficiency for partners using technologies such as Classical and Deep Learning-based Computer Vision, Automatic Speech Recognition (ASR), Text-to-Speech (TTS), and Retrieval Augmented Generation (RAG). As an expert in Speech AI, you will handle tasks including ASR models, Voice Activity Detection, Language/Emotion Detection, and Speaker Diarization.

Responsibilities

• Pipeline Implementation: Implement end-to-end speech processing pipelines for various projects.
  

• Technical Research: Stay updated on the latest achievements and research in Machine Learning.
  

• Scalable Coding: Write performant, high-quality code that can be easily deployed to thousands of mobile robotic units.
  

• Cross-Language Integration: Work with Python for general AI codebases and C++ for programs intended to run on edge hardware (Jetson boards).
  

Requirements

Requirements

• Programming: Proficiency in Python and a solid knowledge of C/C++.
  

• DevOps Tools: Experience with versio control (Git) and containerization (Docker or Podman).
  

• Deep Learning Fundamentals: * Mastery of neural network architectures such as Encoder-Decoder, Transformers, and RNNs.
  

  • Understanding of core ML concepts including supervised/unsupervised training, classification, and regression.
    

  • Familiarity with evaluation metrics like WER/CER and Cross Entropy.
    

• Speech AI Expertise: * Knowledge of audio preprocessing, Voice Activity Detection (VAD), and Speaker Diarization.
  

  • Proficiency with libraries such as the HuggingFace ecosystem, OpenAI Whisper, and NeMo.
    

• Education: Master’s degree in Computer Science, Deep Learning, or a related technical field.
  

• Deployment Experience: Practical experience deploying Speech AI systems, including ASR and Emotion Detection.
  

• ASR Specifics: Knowledge of model distillation, fine-tuning strategies, and model evaluation.
  

• Advanced Systems: Familiarity with distributed systems, cloud computing, and high-performance computing (HPC).
  

• Specialized Hardware: Exposure to NVIDIA technologies such as CUDA, TensorRT, or Triton.
  

• Language: Ability to read and write Japanese.
  

Benefits

Work Environment:

• Schedule: Flex working schedule (8 hours/day) between 07:00 and 22:00.
  

• Remote Work: 2 days per week remote, with potential expansion up to 4 days based on performance.
  

• Leave: A long holiday policy allowing up to 1 month of continuous leave.
  

• Language: A fully English-speaking work environment within the technology team.
  

• Culture: Monthly or quarterly company-sponsored team meals and recreational events (BBQs, training camps, etc.).
  

  
  

Benefit Program:

• Paid Leave: 15 days of paid leave annually, cumulative for up to 2 years.
  

• Allowances: * Housing: 30,000 yen/month
  

  • Child: 10,000 yen/child/month (up to 2 children, until 14 years of age).
    

  • Commuter: Full allowance between home and the closest station to the office.
    

  • Late-night: Additional allowance for work performed after 10:00 PM.
    

• Professional Development: Learning Development Credit Program worth up to 30,000 yen/year for career-related growth.
  

• Insurance: Comprehensive Health, Pension, and Employment insurance
  

• Family Support: Maternity and paternity leave for up to 1 year (available after 1 year of employment).