Open to opportunities

Sivaji Alla

@sivajialla

Message

I optimize edge and cloud machine learning systems for faster, reliable deployment.

United States

Message

What I'm looking for

I'm looking to build and deploy production AI/ML systems across edge hardware, cloud platforms, and enterprise workflows, with opportunities to improve model performance, automate ML operations, and collaborate with hardware, software, and product teams.

At Qualcomm, I build cross-platform deep learning benchmarking and regression-testing systems across CPU, GPU, and Qualcomm Hexagon NPU. My work reduced manual performance testing by 70%, improved on-device inference speed by 45%, and detected 95% of performance regressions before production.

Previously at JPMorgan Chase, I built AWS ETL workflows processing 5M+ records daily and automated monitoring that reduced incident detection time by 50%. At Hexagon, I delivered real-time defect-detection and sensor-fusion pipelines for manufacturing, achieving 94% precision at 45ms edge latency.

I also developed credit-risk and fraud-detection models at HSBC, combining Python, Scikit-learn, and XGBoost to achieve 80% accuracy and a 0.94 AUC-ROC. I enjoy turning ML models into measurable, production-ready systems across edge hardware, cloud data pipelines, and enterprise platforms.

Experience

Work history, roles, and key accomplishments

Current

AI/ML Engineer

Current

Qualcomm

Nov 2025 - Present (9 months)

Engineered a cross-platform benchmarking framework to profile deep learning inference across CPU, GPU, and Qualcomm Hexagon NPU cores, reducing manual performance-testing effort by 70%. Optimized model inference using INT8/FP16 quantization, improving on-device speed by 45% and reducing memory footprint by 35%.