8 часов назад
Audio Machine Learning Data Engineer
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Audio Machine Learning Data Engineer (Python/TensorFlow/Keras): Developing and managing audio datasets and data pipelines for machine learning applications with an accent on data collection, curation, labeling, cleaning, augmentation, and dataset quality. Focus on building scalable automated tooling, deploying models to resource-constrained DSP and embedded platforms, and validating audio data across diverse datasets.
Location: Lausanne, Switzerland
Company
develops hardware and software products that support collaboration, productivity, and audio experiences.
What you will do
- Develop and manage audio datasets and machine learning data pipelines.
- Design and maintain pipelines for audio data collection, curation, labeling, cleaning, and augmentation.
- Collaborate on the development and deployment of audio machine learning models for Tensilica DSP, ARM, and RISC-V platforms.
- Build automated tools to monitor audio data quality and statistical diversity.
- Establish versioned and documented datasets for model training, validation, and benchmarking.
- Develop continuous improvement strategies for existing datasets and scalable augmentation methods.
Requirements
- At least 3 years of direct experience working with extensive audio datasets, including augmentation and preprocessing.
- Strong Python proficiency for machine learning development and data pipeline automation.
- Experience building scalable data pipelines for large and complex datasets.
- Expertise with TensorFlow and Keras.
- Bachelor’s or Master’s degree in Electrical Engineering, Computer Science, or a related discipline, or equivalent practical experience.
- Strong communication, documentation, collaboration, and leadership skills.
Nice to have
- Expert-level audio analysis skills, including listening tests and artifact detection.
- Experience designing and statistically analyzing objective and subjective audio quality evaluations.
- Proficiency in C and SQL.
- Experience with Git and data-driven quality validation across diverse datasets.
Culture & Benefits
- Inclusive and collaborative working environment focused on equality and sustainability.
- Flexible working environments and hybrid work models are available across , depending on the team and location.
- Comprehensive benefits packages that vary by location.
- Support for physical, financial, emotional, intellectual, and social wellbeing.
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