Machine Learning Engineer
Tasks
- Architect ML systems
- Build ML systems
- Build data pipelines
- Create decoding strategies
- Deploy ML systems
- Design model architectures
- Develop loss functions
- Fine-tune large language models
- Implement ML evaluation frameworks
- Implement training and inference strategies
- Improve model robustness
- Mentor engineers
- Monitor model performance
- Own end-to-end ML lifecycle
- Resolve data quality issues
- Resolve scaling issues
- Set ML infrastructure best practices
Perks/Benefits
- N/A
Skills/Tech-stack
Automatic Speech Recognition | Cloud deployment | Conversational Datasets | Data Augmentation | Data Preprocessing | Decoding | Evaluation Frameworks | Fine Tuning | Inference | JAX | Language Models | Language Processing | Large Language Models | Loss Functions | Machine Learning | Model Architecture | Model Monitoring | Model Serving | Model Training | Model versioning | Natural Language | Natural Language Processing | Observability | Performance Regression Detection | Performance regression | PyTorch | Regression Detection | Rollback strategies | Speech Recognition | Speech datasets | Text to Speech
Education
Regions
Countries
States
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