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Shivani Sharma
Mid-Level Software Engineer specializing in Cloud, DevOps, and MLOps
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About
Built and productionized a recommendation system from notebook prototype into a low-latency, scalable Cloud Run service using Docker, FastAPI, Terraform, CI/CD (GitHub Actions), and MLOps tooling (Vertex AI, MLflow). Experienced diagnosing real-time workflow issues using structured logging/ELK and GCP metrics, including resolving intermittent 504s by fixing unbounded SQL and adding caching. Also partners with sales/customer teams (Wasabi) to deliver tailored demos, troubleshoot, and drive onboarding/adoption.
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Key Strengths
- End-to-end ML system productionization (notebook prototype to scalable service)
- Strong MLOps practices (model training and versioning with Vertex AI and MLflow)
- Cloud-native deployment and infrastructure automation (Cloud Run, Terraform, Docker)
- Performance troubleshooting and latency reduction via SQL optimization and caching
- Operational rigor: structured logging/telemetry, rollback, and regression test prevention
- Effective technical enablement through live demos and workshops tailored to mixed audiences
- Bridges technical and non-technical stakeholders; supports sales/customer adoption via demos and troubleshooting
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