Rahul R

Machine Learning Engineer with 1.5+ years building production ML for industrial and critical-infrastructure systems — ICS/OT anomaly detection, computer vision, and MLOps. IEEE Best Paper author (92% accuracy aerial-imagery segmentation) with hands-on delivery using TensorFlow, PyTorch, Docker, MLflow, and real-time monitoring pipelines.

Seeking Machine

Learning, MLOps, and Computer Vision Engineer roles on applied, deployment-focused teams.

Machine Learning Engineer (ICS/OT Security) - Safekrit India

(2025-02 - 2026-02)

• Architected an end-to-end Digital Twin platform for industrial (ICS/OT) cybersecurity, modeling a 6-stage water-treatment process across 51 SCADA streams (24 sensors + 27 actuators) sampled at 1-second resolution.
• Engineered ML-based anomaly detection benchmarked against 41 simulated cyber-physical attacks spanning both IT and OT threat vectors across realistic multi-day scenarios.
• Built an end-to-end MLOps pipeline (sensor ingestion → anomaly flagging → visualization) using Python, Flask, MLflow, Docker, InfluxDB, and Grafana with a real-time operator dashboard.

Software Engineer (ML / Computer Vision) - Quinnel Soft Pvt. Ltd

(2024-08 - 2025-01)

• Engineered a real-time monitoring dashboard ingesting live industrial sensor streams and flagging operational anomalies with ML models for continuous plant-health visibility.
• Built an OCR + object-detection pipeline (OpenCV, TensorFlow) that auto-generated React.js UI components from HMI engineering diagrams, cutting manual UI development effort by 80%.
• Containerized the model and application lifecycle with Docker and served inference via Flask, enabling repeatable deployment across environments.

M.E. - Computer Science Engineering - St. Joseph's College of Engineering (2025 - Present)

B.E. - Electronics & Communication Engineering - St. Joseph's College of Engineering (2021 - 2024)