Senior Machine Learning Engineer - AI/ML
Tasks
- Architect scalable secure ML platform
- Build hyperparameter tuning pipelines
- Build model ready data pipelines
- Define reproducibility and governance best practices
- Enable experiment tracking and model registry
- Ensure security, privacy, and regulatory compliance
- Establish ML CI CD practices
- Implement ML training infrastructure
- Lead technical discussions and mentor engineers
- Monitor model performance and drift
- Optimize ML workload performance
- Orchestrate ML workflows
Perks/Benefits
- Continual development
- Flexible work environment
- Health and wellness benefits
- Internal career growth
- Paid relocation orientation process
- Paid time off
- Volunteer time off
Skills/Tech-stack
AWS | Airflow | Apache Flink | Apache Spark | Argo Workflows | Cloud platform | Databricks | Distributed Systems | Docker | Drift Detection | Experiment tracking | Feast | Feature Store | Go | Google Cloud | Google Cloud Platform | Hyperparameter Tuning | Java | Kafka | Kubeflow | Kubernetes | MLOps | MLflow | Machine Learning | Microservices | Microsoft Azure | Model Drift | Model Drift Detection | Model Governance | Model Monitoring | Model Registry | Neural Networks | Python | Random Forest | SageMaker | Spark Structured Streaming | Statistical Learning | Structured Streaming | TeamCity | Tecton | Terraform | Transformers | Vertex AI | XGBoost
Education
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