Machine Learning Engineer
Tasks
- Architect scalable data pipelines
- Automate deployment with CI CD infrastructure as code and containers
- Build feature stores for batch and real time
- Build reproducible ML training evaluation and inference workflows
- Create documentation dashboards and runbooks
- Drive problems to completion
- Integrate event streams into analytics ready datasets
- Monitor test and improve data quality model performance latency and cost
- Partner with product data science and security teams to ship compliant services
Perks/Benefits
- 401k retirement savings
- Health care insurance
- Occasional travel for meetings
- Paid parental leave
- Paid sick time
- Paid time off
- Remote work
- Retirement savings program
- Wellness leave
Skills/Tech-stack
AWS | Airflow | Amazon Redshift | Amazon SageMaker | Apache Flink | Apache Spark | Azure | BigQuery | CI/CD | Container Orchestration | Dagster | Data Modeling | Data Quality | Distributed Computing | Docker | ELT | ETL | GCP | Infrastructure as Code | Kafka Streams | Kubernetes | MLflow | Model Evaluation | Model Inference | Python | SQL | Snowflake | Vector Databases | Vertex AI | “as-code”
Education
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