Senior ML Engineer - Offline Team
Tasks
- Build and maintain data and ML pipelines
- Enable Data Scientists with reusable pipeline components
- Implement deep learning training loops with PyTorch
- Improve scalability and reliability with infrastructure collaboration
- Maintain reproducibility across the ML lifecycle
- Manage experiment tracking and versioned configs
- Mentor team members and share engineering knowledge
- Optimize training pipelines for performance memory and cost
- Support CI CD migrations
- Support model deployment and production monitoring
- Take end to end ownership from ideation to production release
- Triages and resolves alerts from Airflow dbt and related systems
Perks/Benefits
- N/A
Skills/Tech-stack
Amazon Web Services | Apache Airflow | Apache Spark | Batch inference | DBT | Data Preprocessing | Experiment tracking | Feature Engineering | Hyperparameter Tuning | Kubernetes | Latency optimization | LightGBM | MLflow | Model Deployment | Model Serving | Prometheus | PyTorch | Python | Real Time | Real-time Inference | Reproducibility | Scikit-learn | Terraform | Web Services
Education
N/A
Regions
States
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