Machine Learning Engineer, Infra (MLOps) - CN
Tasks
- Apply DevOps practices to ML workflows
- Build automated training pipelines
- Build feature pipelines for training and inference
- Design model training infrastructure
- Detect data quality issues
- Develop model serving and inference systems
- Ensure reproducibility and versioning
- Implement CI/CD for ML pipelines
- Implement observability and monitoring
- Monitor model anomalies and regressions
- Optimize distributed training and resource scheduling
- Orchestrate model training workflows
Perks/Benefits
- N/A
Skills/Tech-stack
Apache Airflow | Apache Spark | Automated testing | CI/CD | Dataset Management | DevOps | Distributed Training | Feature Engineering | GRPC | Infrastructure as Code | Kafka | Kubernetes | Machine Learning | Model Serving | Model versioning | Monitoring | Observability | Online Inference | Prefect | PyTorch | Python | REST | Ray | Recommendation Systems | Reproducibility | TensorFlow | Workflow Orchestration | “as-code”
Education
N/A
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