G*****a

● Built RAG pipelines over internal test logs with LLM reasoning, reducing fault triage time for engineers. ● Designed multi-agent workflows that automatically flag anomalies, recommend fixes, and adapt test plans in real time, cutting manual investigation effort by 40%. ● Fine-tuned BERT/GPT models on proprietary failure logs for context-aware diagnostics and prioritized resolution paths. ● Deployed lightweight on-device ML models via Qualcomm AI SDK, enabling low-latency inference on test hardware. ● Integrated RAG/ML services into CI/CD (Jenkins/Git) with automated checks, improving deployment reliability and observability.

● Developed Python automation APIs and test suites for Dual/Solo embedded medical devices, improving test reliability and coverage. ● Implemented a PyTest-based functional and integration framework that cut manual regression effort by 80%. ● Integrated tests into Jenkins CI/CD pipelines, enabling auto-triggered builds, faster failures, and smoother release cycles. ● Applied pandas/NumPy log analysis to uncover recurring defect patterns and prioritize high-risk scenarios. ● Prototyped simple anomaly-detection models on device telemetry to surface likely failure cases earlier in testing.