MLOps Engineer
USD 140K-180K (estimate) Senior-level Full Time
Tasks
- Build inference pipelines
- Build real time data connectors
- Deploy, monitor ML models
- Design build maintain ETL pipelines
- Develop REST APIs
- Document systems and create runbooks
- Ensure data quality and lineage
- Implement data validation, monitoring, and alerting
- Implement model versioning A B testing and rollback
- Integrate data capabilities into mobile and web applications
- Maintain protocol compliance data pipelines
- Optimize model performance for cost efficiency
- Productionize data science outputs
- Translate research code into production systems
Perks/Benefits
- 401k matching
- Dental insurance
- Educational expenses
- Flexible PTO
- Flexible spending account
- Health insurance
- Life and AD D coverage
- Paid Holidays
- Professional development support
- Vision insurance
Skills/Tech-stack
A/B | A/B Testing | AWS Lambda | AWS Step Functions | Airflow | Amazon EC2 | Amazon RDS | Amazon S3 | Amazon SageMaker | B testing | Data Lineage | Data Processing | Data Validation | ETL | Geospatial Data | Geospatial Data Processing | Google Cloud | Google Vertex | Google Vertex AI | Inference Pipelines | MLflow | Machine Learning | Model versioning | Monitoring | Prefect | Python | REST APIs | Remote Sensing | Rollback | SQL | Satellite imagery | Series data | Step Functions | Time Series | Time Series Data | Vertex AI
Education
N/A
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