Machine Learning Internship in Delhi at ESSI Integrated Technologies
Machine Learning
ESSI Integrated TechnologiesLocation(s): DelhiDESCRIPTION
About the internship
Selected intern's day-to-day responsibilites include:
1. Assist in designing and developing intelligent video analytics systems for vehicle detection, face recognition, crowd monitoring, and vehicle identification.
2. Support the development and optimization of YOLO-based detection, OCR, and night vision enhancement pipelines.
3. Contribute to microservice-based AI architectures using FastAPI, Kafka, Redis, and WebSocket.
4. Explore Generative AI and Vision-Language Models for semantic video understanding.
5. Participate in the full development lifecycle - data preparation, model prototyping, integration, testing, and documentation.
6. Collaborate with senior engineers to integrate AI components into live CCTV and monitoring systems.
7. Maintain code quality, ensure reproducibility, and contribute to system scalability.
8. Stay updated with recent advances in computer vision and AI system design.
Skill(s) required
Who can apply
Only those candidates can apply who:
1. are available for full time (in-office) internship
2. can start the internship between 29th Oct'25 and 3rd Dec'25
3. are available for duration of 6 months
4. have relevant skills and interests
Other requirements
1. Familiarity with object detection models (e.g., YOLO v5–v8 or similar).
2. Experience implementing OCR pipelines (EasyOCR, Tesseract, or custom models).
3. Understanding of low-light image enhancement and night vision preprocessing.
4. Proficiency in Python and familiarity with PyTorch, TensorFlow, OpenCV, and FastAPI.
5. Knowledge of REST API design and microservices concepts.
6. Exposure to Docker, containerized deployment, and real-time data streaming (Kafka, Redis, WebSocket).
7. Understanding of the ML pipeline — preprocessing, training, evaluation, and deployment.
8. Awareness of distributed system design and version control (Git).
9. Pursuing or recently completed B.Tech/M.Tech/PhD in Computer Science, AI, or Data Science.
10. Prior project or internship experience in AI/ML, computer vision, or deep learning.
11. Exposure to CCTV surveillance, face recognition, or video analytics.
12. Familiarity with SQL/NoSQL databases for data handling.
13. Awareness of LLMs or VLMs for semantic video search and multimodal AI.
14. Knowledge of RetinaFace, ArcFace, or AdaFace models.
15. Interest in deploying AI at the edge for real-time feeds.
16. Familiarity with Kubernetes, CI/CD, and performance optimization.
17. Awareness of privacy, fairness, and bias mitigation in AI systems.
Perks
1. CCTV surveillance and smart monitoring systems.
2. Vehicle detection, classification, and license plate recognition (OCR).
3. Night vision enhancement for low-light CCTV feeds.
4. Face recognition system (FRS) integration.
5. Crowd analysis and anomaly detection.
6. Semantic video understanding via VLMs.
7. Fully dockerized ecosystem using Kafka, Redis, and WebSocket for real-time processing.
B. Other Rewards:
1. Hands-on experience with real-world AI/ML video analytics systems.
2. Mentorship from experienced AI engineers and system architects.
3. Exposure to full-stack deployment pipelines and edge AI systems.
4. Opportunity to convert to a full-time role based on performance and project outcomes.