Machine Learning Engineer
Tasks
- Deploy and monitor ML models in production
- Design, build, and maintain scalable ML systems
- Develop and optimize ML pipelines
- Ensure data quality observability and performance
- Implement MLOps practices
- Integrate ML models into real time products
- Stay current with AI infrastructure tooling and research
Perks/Benefits
- Healthcare, Dental and Vision coverage
- Ownership and autonomy
- Rapid iteration
- Work with top engineers
Skills/Tech-stack
AWS | Airflow | Audio Processing | Azure | CI/CD | Continuous Monitoring | Dagster | Data Ingestion | Data Preprocessing | Data Validation | Data labeling | Deep learning | Docker | Experiment tracking | GCP | Generative AI | Go | Kubeflow | Kubernetes | Language Models | Language Processing | Large Language Models | MLOps | MLflow | Machine Learning | Model Deployment | Model Testing | Model Training | Model versioning | Natural Language | Natural Language Processing | Prefect | Python | Real Time | Real-time Inference | Speech Recognition | Text to Speech | Weights and Biases
Education
N/A
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