Senior Machine Learning Engineer, DevOps/SRE
Tasks
- Accelerate ML experimentation and deployment
- Architect CI CD systems for ML models
- Automate MLOps and SRE best practices
- Build GPU TPU training and inference environments
- Design scalable production ML infrastructure
- Implement observability for ML systems
- Improve safe reliable production releases
- Lead incident response
- Manage pipeline health metrics
- Monitor model performance and drift
- Operate cloud infrastructure for ML workloads
- Own real time model inference infrastructure
- Perform root cause analysis
- Streamline end to end ML lifecycle
Perks/Benefits
- Financial wellness support
- Healthcare benefits
- Life and disability insurance
- Mental health support
- Paid time off
- Retirement options
Skills/Tech-stack
Aerospike | Amazon Web Services | Apache Airflow | Apache Arrow | Apache Flink | Apache Spark | CI/CD | Chronon | Cloud platform | Datadog | Datadog APM | Disaster Recovery | Drift Detection | EKS | GKE | GitLab Runner | Google Cloud | Google Cloud Platform | Grafana | Infrastructure as Code | Java | Jenkins | KV store | Kafka | Kubernetes | MLflow | Model Drift | Model Drift Detection | Model Monitoring | Observability | Prometheus | Python | Ray | Scala | Terraform | Vector Databases | Web Services | “as-code”
Education
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