MLOps Engineer
- Build scalable ETL/ELT pipelines
- Collaborate with data scientists to bridge experimentation and production
- Convert notebooks and prototype code into production grade solutions
- Create curated datasets for data science and machine learning
- Create reusable frameworks for efficient model deployment
- Design and implement reliable data pipelines for machine learning and analytical workloads
- Design build and maintain production grade MLOps pipelines
- Develop monitoring for model performance data quality data drift and operational health
- Develop reusable data transformation frameworks
- Establish and improve CI CD practices for machine learning workloads
- Implement data validation and data quality controls
- Implement logging, monitoring, and error handling
- Implement model versioning artifact management experiment tracking and reproducibility
- Integrate structured and unstructured data from multiple sources
- Optimize pipelines for performance, scalability, and cost
- Productionize machine learning models
- Support batch and event driven or streaming workloads
- Translate data science requirements into scalable engineering solutions
- Troubleshoot production machine learning pipelines
Perks/Benefits:
- 401k retirement plan
- Employee assistance program
- Health savings account
- Life insurance
- Long-term disability
- Medical/Dental/Vision
- PTO
- Short-term disability
- Transportation benefits