Responsibilities:

Responsible for developing courses in undergraduate- and graduate-level training in AI, machine learning, data science, decision optimization.
Responsible for creating course content, texts, videos, assignments, technique-driven projects, use-case driven projects, and interactive playgrounds.
Conduct live lectures, webinars, doubt clearing sessions, special lectures, paper presentations, code walkthroughs, and hands-on coding sessions.
Build long-term academic and industry partnerships in India and abroad.
Participate in national and international conferences and workshops in AI, genAI, and machine learning.

Required Skills and Experience:

Strong theoretical, implementation and practical (applied) skills in the following:
Mathematical foundations of AI, ML, deep learning, data science
Modern neural architectures, optimizations, learning techniques
Novel learning methods for limited-data or compute-limited scenarios
Graph neural networks and large-scale graph machine learning
Transformer architectures and applications in language and vision
Physics-inspired deep learning and diffusion models
Modern LLM optimization techniques, compression, quantization
Scientific and industrial applications of AI
Exposure to next-gen futuristic research in AI based planning, reasoning, agent-based automations, and quantum computing

Ability to elucidate complex mathematical and abstract ideas into easy to grasp concepts while maintaining mathematical rigor and consistency.
Ability to formulate mathematical models from real world problems and data.
Ability to convert concepts into programmable models and algorithms into code.
Ability to define programming assignments and data- or model-driven projects
Experience with curriculum development, pedagogical methods, research.
Strong communication skills to coordinate with various stakeholders including academicians, corporate executives, students, and government officials.

Qualifications:

MS/Ph.D. in AI, ML, Mathematics, Computer Science, Electrical Engineering, or any other intersecting area, with 2+ years of academic or industry research experience in developing AI solutions for real-world problems.
Ability to implement solutions to real world computational problems or use cases using QpiAI proprietary libraries and other open source ML packages.
Ability to contribute code to development of libraries, codebases, and integrators for quantum system-level software and application-level software.
Excellent track record in AI or Machine Learning research demonstrated by peer-reviewed publications, patents, and independent or collaborative projects.
Strong understanding of AI/ML applications in industrial automation, robotics, self driving cars, pharmaceuticals and materials, logistics, supply chain management, financial services, retail, digital commerce, and other sectors

AI and Machine Learning Trainer