Machine Learning Engineer - Voice Conversion
Tasks
- Architect large scale speech models
- Build development tooling
- Contribute safety consent guardrails
- Create listening tests and quality metrics
- Design experiments and analyze results
- Evaluate robustness and bias
- Harden training evaluation inference pipelines
- Implement monitoring and rollback
- Implement synthetic data strategies
- Measure SV WER ASR based performance
- Mitigate misuse and abuse
- Own data requirements and data curation
- Pre train and fine tune speech models
- Profile latency memory and cost
Perks/Benefits
- 401k retirement plan
- Company equity
- Fertility support
- Lifestyle spending account
- Meals and snacks
- Medical/Dental/Vision insurance
- One Medical membership
- Paid time off
- Parental leave
Skills/Tech-stack
Adversarial Training | Audio CODEC | Audio Variational Autoencoder | Bias Testing | CUDA | DPO | Data Augmentation | DeepSpeed | Diffusion Models | Distributed Training | Evaluation | FSDP | Flow matching | GRPO | Language Models | Language Processing | Large Language Models | Latency optimization | Machine Learning | Memory Optimization | Model Alignment | Natural Language | Natural Language Processing | Neural Audio Codec | Production Monitoring | PyTorch | Robustness Testing | Speech Recognition | Synthetic data | Text to Speech | Transformer | Variational Autoencoder | Vocoder
Education
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