Position
AI Engineer Speech Processing
- Information
Job Description
At NABLAS, our main mission is to solve challenging problems using the most suitable machine-learning techniques for various types of data. As a Researcher/Research Engineer, you will be involved in multiple projects and collaborate closely with other staff members. Your responsibilities will vary based on your experience and aptitude.
Key responsibilities:
- Conducting surveys, prototyping, implementing machine learning/deep learning models, and validation for R&D projects.
- Designing new algorithms.
- Conducting technical surveys.
- Developing applications and libraries.
- Building and managing HPC environments and hardware.
- Project management.
- Providing guidance and education.
- Creating documentation and presentations.
In your role, you will work with data and technologies such as:
- Audio data.
- Sensor data.
- Image and text data.
- Signal processing, and more.
Key Requirements
- A master's or doctoral degree, or equivalent knowledge, in fields such as AI, computational science, or information science.
- Experience in tasks related to audio processing or signal processing (e.g., FFT, wavelet analysis, mel spectrogram analysis, development of deep learning or machine learning methods for audio data).
- Experience in creating machine learning algorithms.
- Over 3 years of coding experience in Python (Numpy, Scipy, Scikit-learn).
- Experience using communication tools such as Slack, Google Drive, Trello, and JIRA.
Additional skills
- Broad knowledge of speech processing technologies such as WaveNet, WaveRNN, Tacotron, SV2TTS, and other deep learning techniques.
- Experience in creating speech signal datasets.
- Experience in developing deep learning algorithms based on CNNs, GANs, and generative models.
- Proficiency in using tools such as PyTorch, TorchAudio, TensorFlow, and OpenCV.
- Experience with MLOps technologies.
- Experience using development tools such as IDEs, debuggers, Jupyter Notebooks, and Git.
- Experience working on application system development projects.
- Participation or awards in data analysis competitions like Kaggle.
- Participation or awards in competitive programming platforms like AtCoder.音声処理に関する幅広い知識 （WaveNet, WaveRNN, Tacotron, SV2TTSや、その他の深層学習系技術など）
- 音声信号データセットの作成経験
- CNNやGAN、生成モデルをベースとした深層学習アルゴリズムの開発経験
- PyTorch, TorchAudio, TensorFlow, OpenCVなどの利用経験
- MLOps技術に関する利用経験
- IDE, デバッガ, Jupyter, Gitなどの開発ツールの利用経験
- アプリケーションシステム開発プロジェクトに従事した経験
- Kaggleなどのデータ分析コンペティションの参加・受賞経験
- AtCoderなどの競技プログラミングの参加・受賞経験
-Information
Contract
Full-time / Outsourcing (negotiable)
Salary
• Determined based on experience and ability
• Salary increases: Available (as needed)
• Bonuses: Twice a year (based on performance and results)
• Incentives: Available (e.g., sales incentives)
Location
Full remote is available.
Office : 1F Hongo Tsuna Building, 6-17-9 Hongo, Bunkyo-ku, Tokyo
Work Hours
Flextime system (core time / 10:30 - 16:00)
*Depends on employment status
Holidays
• Full two-day weekends (Saturday, Sunday, and public holidays)
• Year-end/New Year company holidays (December 30 - January 3)
• Paid leave: 20+ days annually
Example (first year):
- Joining Special leave: 5 days (granted on the date of hire)
- Annual paid leave: 10 days
(granted after 6 months of employment)
* From the second year: 16+ days granted annually
- Refresh leave: 5 days/year
• Other leave: Parental leave, maternity leave
• Bereavement leave
*Depends on employment status
Allowances
• Office Attendance Allowance: Provided when working in-office
• Commuting Allowance: Full transportation expenses covered
• Remote Work Allowance: Provided when working remotely
• Position Allowance
• Overtime Allowance: Paid based on actual working hours
*Depends on employment status
Benefits
・Social insurance
・Corporate defined contribution pension plan
・Book purchase system
・Kaggle and AtCoder support system
・Use of Kilter Board
*Depends on employment status