Machine Learning Systems & Infrastructure Engineer
Tasks
- Build data ingestion pipelines
- Build machine learning training systems
- Debug distributed training across GPUs
- Develop workflow orchestration pipelines
- Enable distributed training
- Handle secrets IAM and network boundaries
- Implement monitoring, logging, and alerting
- Maintain CI/CD pipelines
- Maintain dataset loaders and checkpointing
- Manage infrastructure as code with Terraform
- Optimize GPU compute performance
- Orchestrate machine learning experiments
- Serve machine learning models in production
Perks/Benefits
- N/A
Skills/Tech-stack
AWS IAM | Airflow | Amazon Web Services | Azure Networking | BigQuery | CI/CD | CUDA | Cloud platform | DDP | Data Versioning | Distributed Training | Docker | Experiment tracking | FSDP | GCP IAM | GPU scheduling | Google Cloud | Google Cloud Platform | Grafana | IAM | Kubeflow Pipelines | Kubernetes | MLflow | Machine Learning | Microsoft Azure | Modal | NCCL | Object storage | Observability | OpenTelemetry | PostgreSQL | Prometheus | PyTorch | PyTorch distributed | Python | SQL | SQLite | Slurm | Snowflake | Terraform | Triton | Volcano | Web Services | Weights and Biases
Education
N/A
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