ML Engineer -Signal Processing / ASR
Tasks
- Collaborate with product and engineering to deliver practical ML solutions
- Debug model quality issues using data analysis and production monitoring
- Design build and improve ASR audio and speech ML systems for production
- Develop signal processing pipelines for real world audio
- Optimize inference for latency throughput cost and reliability
- Own ML workflows end to end data preparation model training validation inference monitoring
- Train fine tune evaluate and deploy ASR and audio ML models
Perks/Benefits
- N/A
Skills/Tech-stack
Audio classification | Automatic Speech Recognition | CPU Utilization | Cost Optimization | Data Analysis | Data Preparation | Docker | Domain Drift | FastAPI | GPU Utilization | Inference Server | JAX | Kubernetes | Latency optimization | Model Evaluation | Model Inference | Model Monitoring | Model Training | Noisy Labels | ONNX Runtime | Observability | PyTorch | Python | Regression testing | Signal Processing | Speaker Diarization | Speech Recognition | TensorFlow | Throughput Optimization | Torchserve | Triton Inference | Triton Inference Server | VAD
Education
N/A
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