MLOps Engineer
Tasks
- Apply testing code review CI CD
- Build data preprocessing and feature engineering pipelines
- Build model serving services
- Build shared libraries and utilities
- Collaborate with data science and engineering teams
- Containerize and deploy services
- Create reproducible training and batch inference pipelines
- Diagnose production incidents and drive fixes
- Document pipelines and runbooks
- Ensure feature parity across training batch and real time
- Implement parity checks and reconciliation
- Manage model artifacts and versioning
- Monitor model performance drift and data quality
- Operationalize machine learning solutions
Perks/Benefits
- 401k plan
- Dental insurance
- Disability insurance
- Free Time PTO
- Health insurance
- Life insurance
- Paid Holidays
- Parental leave
- Vision insurance
Skills/Tech-stack
Airflow | Apache Spark | Authentication | Authorization | Celery | Data Quality | Databricks | Docker | Error Handling | FastAPI | Feature Engineering | Git | GitHub Actions | Input validation | Jenkins | Kafka | Kubernetes | MLflow | Machine Learning | Machine learning lifecycle | Metrics | Model Monitoring | Prediction Drift | Prefect | PySpark | PyTorch | Python | RabbitMQ | Redis Streams | SQL | SQS | Scikit-learn | Shell Scripting | Structured Logging | Tracing | XGBoost
Education
N/A
Roles
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