Senior MLOps Engineer
United States - Remote
R
USD 165K-250K (estimate) Senior-level Full Time
Tasks
- Build LLM delivery pipelines for retrieval orchestration evaluation deployment
- Build and maintain CI CD for ML
- Create feature pipelines and feature stores
- Design ML platforms end to end workflows
- Develop LLM evaluation harnesses with offline and online testing
- Develop training infrastructure for scalable distributed training
- Ensure governance with lineage provenance and approval workflows
- Implement model monitoring and observability
- Implement model registry and experiment tracking
- Implement observability with tracing metrics logs dashboards alerting
- Implement risk scoring and guardrail workflows
- Implement security and privacy controls with IAM and encryption
- Productionize ML models on GCP with containers and orchestration
Perks/Benefits
- Continuous learning opportunities
- Flexible working arrangements
- Health equity mission impact
- Remote or hybrid options
Skills/Tech-stack
AI Pipelines | AI endpoints | API Development | Audit Logs | Autoscaling | CI/CD | Cloud Run | Distributed Training | Docker | Docker images | Encryption | Experiment tracking | Feature Engineering | Feature Store | GCP | GKE | GPU scheduling | IAM | Kubernetes | LLM orchestration | MLOps | Machine Learning | Model Monitoring | Model Registry | Observability | Python | RAG evaluation | Retrieval-Augmented Generation | Secrets management | Vector Search | Vertex AI | Vertex AI Endpoints | Vertex AI Feature Store | Vertex AI Model Registry | Vertex AI pipelines
Education
N/A
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