ML Ops Engineer
Tasks
- Build inference pipelines
- Build machine learning models
- Create reproducible workflows
- Deploy models to production
- Design machine learning solutions
- Develop feature engineering pipelines
- Evaluate models with metrics
- Implement model monitoring
- Iterate on model performance
- Perform error analysis
- Run machine learning experiments
Perks/Benefits
Skills/Tech-stack
AWS | Airflow | Apache Spark | CI/CD | DBT | Data Leakage Prevention | Data leakage | Deep learning | Docker | Experiment design | Feature Engineering | Feature Stores | GRPC | GitLab CI | HTTP APIs | Language Models | Large Language Models | Leakage prevention | MLflow | Machine Learning | Model Packaging | Prompt engineering | PyTorch | Python | Retrieval-Augmented Generation | SQL | Scikit-learn | Statistics | TensorFlow | Vector Search | Weights and Biases | XGBoost
Education
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