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Student Exploration and Experience Development (SEED) is a 12-week internship opportunity at Veolia for students to gain hands-on experience in sustainability and ecological transformation. They will work on real-world projects, receive mentorship from industry professionals, and participate in workshops and networking events. The program aims to nurture talent, promote innovation, and foster meaningful connections between students and industry professionals. Overall, the SEED program provides students with the skills, knowledge, and connections needed to make a positive impact in the industry. A Data Science Intern assists in creating, configuring, and testing AI Agents using various large language models (LLMs) and generative AI techniques. The intern will gain hands-on experience in applying generative AI design, prompt engineering, and multimodal models in a real world business context, while staying updated with the latest industry trends and technologies.
Job Responsibility:
Create, configure, and test AI Agents using various LLMs to solve specific business problems and enhance operational efficiency
Develop and implement prompt engineering strategies and evaluation techniques to optimize agent performance
Stay updated with the latest trends in generative AI, including new models, techniques, and ethical considerations
Collaborate with cross-functional teams to understand business needs and provide AI-driven recommendations and solutions
Prepare and present reports on findings and model outcomes to both technical and non-technical stakeholders, clearly communicating insights and implications
Requirements:
Achieved or working towards a MS degree in Computer Science or computer related field from an accredited institution
Experience developing with Python
Experience with SQL development
Good experience with Git
Familiarity with various LLMs (such as GPTs, Gemini, Claude, LLaMA) and understanding the trade-offs of using each model
Understanding of generative AI and agentic AI design (prompt engineering, multimodal models, tool use)
Basic knowledge of Retrieval-Augmented Generation (RAG)
Familiarity with APIs for interacting with LLMs and other AI services
Familiarity with cloud platforms like GCP
Embrace mentorship through design sessions, code reviews, and community building
Strong analytical and problem-solving skills, with the ability to work with large data sets and derive insights
Ability to translate real-world problems into analytical questions and devise AI-driven solutions
Understanding of the ethical implications of generative AI and commitment to responsible AI practices, including transparency, fairness, and privacy considerations
Good verbal and written communication skills, as the role may involve presenting findings and collaborating with team members
A keen interest in generative AI and machine learning, with a willingness to continuously learn and stay updated with industry trends and technologies
Ability to work independently and manage multiple tasks effectively
Strong attention to detail and commitment to producing high-quality work