Senior Staff MLOps Engineer
Tasks
- Build and maintain end-to-end ML pipelines
- Build and support training environments with experiment tracking and distributed training
- Collaborate with ML engineers and data engineers to streamline MLOps workflows
- Develop automated model deployment workflows with CI CD
- Ensure reliability scalability and maintainability of ML systems
- Implement monitoring and observability for ML systems
- Stand up and manage a feature store
Perks/Benefits
- 401k match
- Cell phone stipend
- Fertility and family building support
- Flexible vacation
- Gender-affirming care
- Health, dental, and vision
- Monthly Food Stipend
- Monthly commuting stipend
- Monthly internet stipend
- Monthly wellness stipend
Skills/Tech-stack
AWS | Apache Airflow | Apache Spark | Bash | CI/CD | Data Quality | Distributed Training | Docker | Drift Detection | Embeddings | Experiment tracking | Feature Store | Git | Google Cloud | Helm | Hyperparameter Tuning | Kubernetes | Machine Learning | Microsoft Azure | Model Deployment | Model Monitoring | Observability | PySpark | PyTorch | Python | Retrieval systems | SQL | Snowflake | TensorFlow | Vector Databases
Education
Roles
Regions
Countries
States
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