Sr. Engineering Manager, MLOps
Palo Alto, California, United States
USD 270K-300K Senior-level Full Time
Tasks
- Align infrastructure investments with real time personalization
- Architect automated ML workflows
- Build and maintain model training deployment serving infrastructure
- Conduct root cause analyses for production failures
- Define MLOps vision and strategy
- Ensure production ML scalability and reliability
- Establish MLOps standards CI CD and testing
- Evaluate build vs buy cloud services
- Monitor LLM ops and vector database trends
- Optimize compute governance and cloud costs
- Recruit mentor and lead ML infrastructure team
- Track infrastructure velocity KPIs
- Translate research needs into engineering requirements
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Amazon SageMaker | Apache Flink | Apache Kafka | Apache Spark | Blue-Green Deployment | Blue/green | CI/CD | Canary Deployment | Docker | Feature Engineering | Feature Store | GPU clusters | Google Vertex | Google Vertex AI | Infrastructure as Code | Kubeflow | Kubernetes | LLMOps | MLOps | Machine Learning | Model versioning | Orchestration | Pulumi | PyTorch | Real Time | Real Time Feature Engineering | TensorFlow | Terraform | Vector Database | Vertex AI | “as-code”
Education
N/A
Regions
Countries
States
Cities
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