Machine Learning Engineer - Audio
Machine Learning Engineer - Audio
Posted on :
24-12-2024
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1 Vacancy
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Job Description
Requirements:
- 4 years of experience in Machine Learning Engineering with a focus on audio or speech processing.
- Strong expertise in TTS systems and voice cloning (e.g. Tacotron WaveNet VITS diffusionbased models).
- Proficiency in audio processing libraries such as Librosa FFmpeg and SoundFile.
- Familiarity with opensource models and frameworks like Hugging Face ESPNet and Fairseq.
- Solid understanding of MLOps tools such as Triton Server Docker and Kubernetes.
- Advanced Python programming skills with experience in frameworks like PyTorch and TensorFlow.
- Handson experience developing APIs using Flask FastAPI or similar frameworks.
- Familiarity with cloud platforms like AWS GCP or Azure.
Responsibilities:
- Train finetune and deploy opensource TTS (TexttoSpeech) and voice cloning models.
- Experiment with stateoftheart architectures optimizing for quality latency and efficiency.
- Implement advanced audio processing techniques to achieve highfidelity outputs.
- Work on tasks like speech enhancement feature extraction and audio transformation.
- Leverage frameworks such as Librosa PyTorch TensorFlow and other DSP tools.
- Design and deploy scalable inference solutions using tools like Triton Server.
- Build and manage automated pipelines for data preprocessing training and deployment.
- Optimize model serving and inference performance for realworld use cases.
- Develop robust APIs or services to integrate ML models into production environments.
- Collaborate with backend and frontend teams to ensure seamless integration.
- Create and maintain data pipelines for largescale audio datasets.
- Ensure efficient workflows for data processing annotation and management.
- Keep abreast of advancements in ML and audio processing technologies tools and frameworks.
- Explore emerging tools for voice synthesis and cloning applying them to enhance projects.
- Bachelors or Masters degree in Computer Science Electrical Engineering or a related field.
- Relevant work experience may substitute for formal education.
Employment Type
Full Time
Key Skills
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