Staff ML Engineer
Tasks
- Build machine learning features for pricing decisions
- Collaborate with product and engineering teams on revenue growth
- Define SLIs and SLOs for ML systems
- Design and maintain distributed ML systems in production
- Develop revenue management applications end to end
- Establish ML testing and data validation strategies
- Implement and validate ML models
- Monitor model performance and drift in production
- Optimize revenue management and pricing using statistical methods
- Structure data pipelines for ML training and inference
Perks/Benefits
- Home office stipend
- Manager training
- Paid parental leave
- Paid time off
- Professional development courses
- Remote always
- Remote-first
- Wellness Fridays
Skills/Tech-stack
AWS | Amazon SageMaker | Apache Airflow | CI/CD | Code review | Data Validation | Distributed Systems | Docker | Drift Detection | Experimental Design | Flink | Kubernetes | MLOps | MLflow | Machine Learning | Model Drift | Model Drift Detection | Model Monitoring | Performance Testing | Python | SLIs | SLOs | SQL | Statistical Analysis | Terraform | Version control
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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