Intern
Pitney Bowes
Noida, Uttar Pradesh, India
At Pitney Bowes, we do the right thing, the right way. As a member of our team, you can too. We have amazing people who are the driving force, the inspiration and foundation of our company. Our thriving culture can be broken down into four components: Client. Team. Win. Innovate. We actively look for prospects who: • Are passionate about client success. • Enjoy collaborating with others. • Strive to exceed expectations. • Move boldly in the quest for superior and best in market solutions. Job Description: A Pitney Bowes Internship prepares students for the rigors of the working world while providing a professional and engaging learning experience. Our internships offer meaningful work with the potential to directly impact our business (learn while doing). In addition to challenging work, interns grow their professional networks. From Day 1, they have the opportunity to network with fellow interns from schools across the country as well as PB employees at all levels of the organization. Our vision is to offer undergraduate and masters students an engaging and thought-provoking learning experience while impacting our business in a meaningful way by: PROJECTS : Interns are spread throughout our businesses. Each intern manager will provide intentional learning objective goals and assign real-life projects to own and drive during the summer SUPPORT : Each intern will be paired up with a mentor who will provide guidance, support, and insight into The PB Way! About the Opportunity: As an AI/LLM Intern, you will assist in the research, development, and testing of AI applications using Large Language Models like GPT, LLaMA, Claude, and others. You’ll work closely with data scientists, product managers, and engineers to build cutting-edge prototypes and contribute to real-world AI-driven systems. Assist in building, fine-tuning, and evaluating LLMs and NLP models. Conduct research on prompt engineering, few-shot learning, and model alignment. Collect, clean, and annotate data for model training and evaluation. Create and test APIs that integrate with LLM-based applications. Explore frameworks like LangChain, LlamaIndex, and HuggingFace Transformers. Collaborate with cross-functional teams to translate business needs into AI solutions. Present findings and prototypes to the team with clarity and documentation.
