Staff Machine Learning Engineer
Tasks
- Architect large scale speech and language systems
- Build and evolve ASR TTS NLP LLM systems
- Deploy and monitor production ML models
- Design model architectures loss functions and decoding strategies
- Improve model performance robustness observability
- Lead training fine tuning post training and inference strategies
- Mentor engineers and review technical designs
- Own end to end ML system lifecycle
- Resolve complex ML issues in model behavior and data quality
- Set technical direction for ML infrastructure data pipelines and evaluation
- Translate research into production scalable systems
Perks/Benefits
- N/A
Skills/Tech-stack
Automatic Speech Recognition | Cloud Computing | Data Augmentation | Data Pipelines | Data Preprocessing | Decoding algorithms | Deep learning | Fine Tuning | Inference | JAX | LLM Engineering | Language Models | Language Processing | Large Language Models | Loss Functions | Machine Learning | Model Deployment | Model Evaluation | Model Monitoring | Model Training | Natural Language | Natural Language Processing | Observability | Performance Regression Detection | Performance regression | PyTorch | Regression Detection | Speech Recognition | Text to Speech
Education
Regions
Countries
States
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