Intern(AI)

Internship Overview:
Are you deeply fascinated by the power of Generative AI to create novel content or the ability of Computer Vision to make sense of the visual world? We're looking for enthusiastic and talented AI Interns passionate about these cutting-edge fields to join our team. This internship offers a unique opportunity to gain hands-on experience by working on real-world projects, contributing to innovative solutions in visual intelligence and content generation, and learning from experienced professionals. You'll play a crucial role in supporting our advanced AI initiatives from data preparation to model deployment.
What You'll Do:
As an AI Intern with a focus on Generative AI and Computer Vision technologies, you'll work closely with our Data Science Engineers, contributing to various stages of the AI development lifecycle. Your responsibilities may include:
• Data Preparation & Annotation: Assist in collecting, cleaning, preprocessing, and annotating large visual and textual datasets tailored for Generative AI and Computer Vision models.
• Model Experimentation & Evaluation: Conduct experiments to test, evaluate, and fine-tune AI models for accuracy, performance, and scalability, with a focus on metrics relevant to generative and visual tasks.
• Research & Exploration: Research the latest advancements, architectures, and techniques in Generative AI (e.g., Transformers, Stable Diffusion, multimodal models) and Computer Vision (e.g., Vision Transformers).
• Prototyping & Implementation: Help in building prototypes and integrating Generative AI, Computer Vision, ML & Automation solutions into existing systems or applications.
• Generative AI Development:
• Assist in evaluating, fine-tuning Large Language Models (LLMs), Diffusion Models for tasks like image synthesis, text generation, code generation, or data augmentation.
• Experiment with prompt engineering techniques to optimize outputs from generative models.
• Explore new patterns, techniques in Agentic workflows, MCP etc
• Explore and implement techniques for controlling generated content and ensuring model safety/alignment.
• Computer Vision Solutions:
• Contribute to the development of Computer Vision models for tasks such as object detection, image segmentation, image classification, facial recognition, or video analysis.
• Work on data augmentation strategies specifically for visual datasets to improve model robustness.
• Implement and evaluate advanced image and video processing techniques.
• Documentation: Maintain clear and concise documentation of experiments, model development processes, and results.
• Collaboration: Actively participate in team discussions, brainstorm new ideas, and collaborate with cross-functional teams to align AI solutions with business objectives.
Who can apply:

Recently completed a Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning
Strong foundational understanding of core AI and Machine Learning concepts and algorithms.
Demonstrated interest or project experience in Generative AI (e.g., LLMs, GANs, VAEs, Diffusion Models) or Computer Vision (e.g., CNNs, object detection, image segmentation)
Proficiency in at least one programming language, preferably Python, and familiarity with relevant libraries related to Generative AI, CV & General Machine Learning / Deep Learning
Excellent analytical and problem-solving skills, with a keen eye for detail in visual data and model outputs.
Strong communication and teamwork skills, with the ability to articulate technical concepts clearly.
A strong desire to learn, adapt, and contribute in a fast-paced environment focused on innovation.

About Cognologix:
Cognologix helps companies disrupt by reimagining their business models and innovate like a Startup. We are at the forefront of digital disruption and take a business first approach to help meet our client’s strategic goals.

We are an Data focused organization helping our clients to deliver their next generation of products in the most efficient, modern and cloud-native way.