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Palash Gharde
Mid-level Software Development Engineer specializing in backend, data engineering, and ML systems
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About
ML/Backend engineer with ServiceNow experience building production-grade inference services on FastAPI with Docker/Kubernetes (autoscaling, health checks) and strong reliability practices (monitoring, retries/timeouts, fallbacks). Delivered measurable improvements including 30% lower API latency and 18% higher model accuracy, and built A/B testing plus drift-triggered retraining loops to keep models stable in production.
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Key Strengths
- Built production-grade ML inference service automating feature engineering to real-time prediction
- Reduced API latency by 30%
- Improved model accuracy by 18%
- Designed resilient microservice deployment with Docker/Kubernetes autoscaling and health checks
- Implemented reliability guardrails (timeouts, retries, fallbacks, idempotency) and load testing
- Established monitoring and feedback loops (A/B testing, drift detection, retraining triggers) to improve reliability
- Strong approach to messy enterprise data: validation, canonical schemas, deduplication, manual-review fallbacks
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