Staff Machine Learning Engineer
Tasks
- Architect data pipelines
- Build ML evaluation workflows
- Build ML inference workflows
- Build ML training workflows
- Conduct code reviews
- Create analytics-ready datasets
- Create dashboards
- Improve data and model cost
- Improve latency
- Integrate CI CD deployment
- Integrate event streams
- Maintain feature stores
- Maintain runbooks
- Monitor data quality
- Operate container orchestration platforms
- Produce documentation
- Test model performance
- Use infrastructure as code
Perks/Benefits
- Generous time off
- Healthcare
- Paid parental leave
- Paid personal time off
- Paid sick time
- Parental leave
- Remote work
- Retirement savings plan
- Wellness leave
Skills/Tech-stack
AWS | Amazon Redshift | Amazon SageMaker | Apache Airflow | Apache Flink | Apache Kafka | Apache Spark | CI/CD | Dagster | Data Modeling | Distributed Computing | Docker | ELT | ETL | GitHub Actions | Google BigQuery | Google Cloud | Google Vertex | Google Vertex AI | Infrastructure as Code | Kafka Streams | Kubernetes | MLflow | Microsoft Azure | Pulumi | Python | SQL | Snowflake | Terraform | Vertex AI | “as-code”
Education
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