Artificial Intelligence Intern

The Artificial Intelligence team at QpiAI builds cutting edge products & solutions for our customers most challenging problems in AI across a variety of industry verticals and domains. The team supports enterprise customers from a variety of industries and strives to deliver exceptional innovative solutions, consistently pushing the boundaries of what is possible with AI.

Some of the key areas where our team is actively working to build novel capabilities include Computer Vision, Transformers and Generative AI, LLMs, Neural Architecture Search, AutoML, Explainable AI and Continual Learning.

Our team is looking for driven individuals who can work alongside our product team for various functions ranging from software testing, functional testing, solution/PoC development, documentation, and relevant areas critical to build successful products in AI & Quantum ML space. Some key traits that our colleagues share:

• Curiosity
• First Principles thinking
• Belief in continuous and sustained self-improvement
• Passion to blaze a trail and innovate in the emerging areas of AI

Key requirements:

• Proficiency with Python and Deep Learning frameworks: TensorFlow, PyTorch, torchvision, openCV, NLTK, SpaCy etc.
• Proficiency in using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and Generative AI (GenAI).
• Solid understanding in building Deep Learning models across domains and data modalities - image, text, audio and video.
• Strong theoretical knowledge of Advanced Deep Learning - Transformers, Generative AI, AutoML, Neural Architecture Search and Model Optimization.
• Prototyping novel AI capabilities - leading to creation of intellectual property and published paper acceptance at prestigious international conferences.
• Recent Graduates of Bachelor/Master's degree in engineering, Computer Science, or Electronics Engineering from IITs/NITs.
• Excellent communication skills.

Good to have:

• Understanding of MERN/MEAN stack.
• Understanding of Linux, AWS/Azure/GCP ecosystem, Dockers, and Kubernetes.
• Understanding of Version Control Systems, Workflow Orchestration, CI/CD pipeline