Ai Engineering Intern

**About Cynapse**

Cynapse is a leading AI software company specializing in enterprise-grade Video Intelligence Solutions Powered by Generative AI, tailored to meet the unique challenges of various industries. Our vertical-specific solutions empower organizations to enhance safety, operational efficiency, and security in complex environments such as roads, seaports, airports, and cities. By combining advanced Vision AI with Generative AI, we continually push the boundaries of video analytics, delivering insights and automation that transform operations.

Led by a global team with a proven track record of scaling startups into market leaders, we foster innovation, collaboration, and diverse perspectives. Headquartered from US, Cynapse serves clients worldwide, redefining what's possible with video intelligence.

We are looking for an AI Engineering Intern (Computer Vision & Deep Learning) to join our Computer Vision Model Engineering Team. This is a unique opportunity to contribute to the development and deployment of cutting-edge AI models by integrating deep learning, software engineering practices, and ML pipelines.

You'll work alongside a dynamic team, gaining hands-on experience and contributing to real-world AI projects that optimize the machine learning lifecycle.

**As an AI Engineering Intern, you will**:

- Gain hands-on experience across the entire deep learning pipeline, including **data preparation, model training, evaluation, and deployment.**:

- **Work closely with engineers**to design, build, and refine deep learning models for various Computer Vision tasks, such as image classification, segmentation, object detection, action recognition, and more.
- Work with **ML pipelines**that support model deployment, assisting with tasks like **model integration, data versioning**, automated training, and testing.
- Contribute to the **optimization**of models and pipelines by conducting experiments, analyzing
- results, and helping to improve model performance.
- Gain exposure to modern tools like **Docker, CI/CD**, and **cloud platforms**to support scalable, reliable model deployment.

**Requirements**:

- Currently pursuing or completed a **Diploma/ Bachelor/ Master's**in **Computer Science, Data Science, Artificial Intelligence, Machine Learning,**or a related field.
- Basic understanding of machine learning concepts, demonstrated through the completion of **at least one hands-on university or online module.**:

- **Proficiency in Python programming**(minimum 6 months of hands-on experience or equivalent AI/ML project experience, including GitHub contributions).
- Familiarity with at least one deep learning framework such as **TensorFlow, PyTorch**, or similar.
- Strong **analytical thinking**and **problem-solving skills**, with an emphasis on **improving software pipelines**.

**Preferred (Bonus Skills)**:

- Familiarity with building and optimizing **ML pipelines**, including **data preprocessing, model training, testing**, and **deployment**.
- Experience in software engineering practices like **version control (Git), CI/CD pipelines**, or **Docker**for containerization.
- Exposure to cloud platforms (AWS, GCP, Azure) for deploying and managing ML models in production.
- Knowledge of **computer vision**concepts and libraries (e.g., OpenCV).
- Interest in exploring advanced topics like **Generative AI, multi-modal learning**, or **real-time video analytics**.

**Duration**:

- Availability: At least **4 days a week**, with a **preference for full-time**commitment.
- Flexible start and end dates to accommodate exams or personal schedules.