Suraj Paul
I am a Machine Learning Engineer and former Machine Learning Lead at Vigilantia Praesidium Pvt. Ltd., where I led the development of AI-driven systems across domains including smart security, agriculture, and automation. During my tenure, I focused on transforming research-level AI into scalable, real-world applications, taking ownership from model design to deployment. I specialize in Deep Learning, Computer Vision, and AI system design, with hands-on experience in building real-time solutions using technologies such as FaceNet, MTCNN, and OpenCV. I also have strong experience in integrating AI with IoT systems (ESP32), enabling seamless interaction between intelligent software and hardware. My work includes active involvement in Research & Development (R&D), where I explored innovative approaches, improved model accuracy, and optimized systems for real-time performance. Additionally, I have implemented secure AI solutions using cryptographic techniques such as ECC and AES, ensuring reliable and secure communication in hardware-integrated environments. I am passionate about building intelligent, real-world systems and continuously exploring advancements in AI, embedded systems, and secure infrastructure. I am currently open to opportunities in Machine Learning, AI, and Computer Vision roles where I can contribute to impactful and scalable solutions.
Hire this person
Send a job offer directly to this candidate
About
Motivated and research-driven BCA (Hons with Research) student with hands-on experience as a Machine Learning Lead, specializing in Python, deep learning, AI, and IoT. Strong expertise in computer vision, API integration, and secure hardware communication using ECC and AES encryption. Proven ability to develop scalable real-world solutions across domains such as smart security, agriculture, and automation, with a focus on Research & Development (R&D) and practical deployment.
Experience
Machine Learning Lead (Internship) at Vigilantia Praesidium Pvt. Ltd. (2025-10-16 – 2026-04-15)
Led development of multiple AI-powered systems across domains including smart security, agriculture, and automation. Designed and trained deep learning models, conducted R&D, and built real-time computer vision pipelines for practical deployment.
- Led development of multiple AI-powered systems across domains including smart security, agriculture, and automation
- Designed and trained deep learning models for face recognition, object detection, and behaviour analysis
- Conducted Research & Development (R&D) to improve model accuracy, optimize performance, and explore innovative AI solutions
- Built real-time computer vision pipelines using FaceNet, MTCNN, and OpenCV for practical deployment
- Developed and deployed systems like smart home security, attendance monitoring, traffic analysis, and agriculture automation
- Integrated IoT devices (ESP32) with AI models for real-world system interaction and control
- Implemented secure communication using ECC and AES-GCM encryption in AI-based IoT systems
- Integrated APIs (Telegram, Firebase) for real-time alerts, cloud storage, and monitoring
- Optimized models for low-latency, real-time inference on laptops and edge devices
- Collaborated with teams to convert research ideas into scalable, production-ready solutions
Education
Bachelor of Computer Applications (Honours) with Research in Computer Applications – Brainware University (2027)
