Staples is business to business. You’re what binds us together.

We’re searching for you: fresh talent with new ideas, innovation, passion, and drive to bring to Staples. We have student and graduate opportunities where you’ll help the Staples, Inc. organization be more successful and productive while building a purposeful career. Whether you are looking for a summer internship, co-op, or an entry-level role, we’ll help you develop the technical and soft skills you need to thrive in the future.

This intern position requires you to be in a hybrid working model (at least 3 days in the office, and 2 days remote) based at the Staples, Inc. Corporate Headquarters in Framingham, MA. 

Target Start Date: June 1, 2026 - August 14, 2026 (11-week program)  

Position Overview:

The AI Engineer Intern will join the team to help reimagine Staples' systems and design the next generation of AI applications. They will collaborate with a team of engineers to develop intelligent AI systems, create prototypes, and bring machine learning applications to production. Responsibilities include writing software leveraging data and AI tooling/frameworks, testing for quality, deploying models to the cloud, and analyzing data to build predictive models, agents, their orchestrations, and AI features. The intern will also be responsible for developing and engineering AI systems and solutions that drive innovation and improve operational efficiency. They will work closely with data scientists, ML engineers, and business stakeholders to translate business needs into robust AI solutions. 

What you'll be doing:

• Design, develop, test, and deploy AI models and systems using various frameworks and tools.
• Research and Development: Stay abreast of the latest advancements in AI/GenIA, explore novel applications, and develop proof-of-concept projects.
• Model Selection and Fine-tuning: Select and fine-tune pre-trained GenAI models (e.g., GPTx, LLaMa x) for specific tasks, including text generation, image creation, code synthesis, etc.
• Data Exploration and Preparation: Prepare and analyze data sets for training and evaluation of GenAI models, ensuring data quality and addressing potential biases.
• Experimentation and Evaluation: Conduct experiments to assess the performance of GenAI models and compare different architectures and approaches.
• Application Integration: Develop and integrate GenAI models into existing or new applications, leveraging frameworks like LangChain for seamless orchestration.
• Collaborate with Cross-Functional Teams: Work closely with data scientists, software engineers, product managers, and designers to bring GenAI solutions to life.
• Contribute to Knowledge Sharing: Document your findings, share best practices, and contribute to the team's knowledge base.
• Monitor and evaluate the performance and accuracy of AI models and systems in production.
• Identify and troubleshoot issues related to data quality, model drift, scalability, and reliability.
• Optimize and automate the AI model lifecycle using MLOps/LLMOps/AgentOps best practices.
• Collaborate with data scientists, ML engineers, and business stakeholders to understand the requirements and objectives of AI projects.
• Research and implement new AI techniques and methodologies to improve the existing solutions and explore new opportunities. 

What’s needed- Basic Qualifications:

• Pursuing a master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field 
• 1+ years of learning/experience in AI/ML, with a strong focus on Generative AI.
• Strong programming skills in Python, along with experience in data manipulation libraries (e.g., Pandas, NumPy).
• Hands-on experience with popular GenAI LLM models (e.g., GPT-4o, Llama, Mixtral), SLMs with Phi/Gamma/Triplex, and frameworks (e.g., LangChain, LangGraph, Autogen, Databricks, LlamaIndex, PyTorch, and long-term memory with Mem0 or similar.
• Strong experience in developing and deploying AI systems using Python, PyTorch, leveraging Databricks, Snowflake, or similar frameworks and tools.
• Strong knowledge of machine learning, deep learning, natural language processing, computer vision, and other AI domains.
• Experience in prompt engineering, data preprocessing, model fine-tuning, and evaluation.
• Experience in using MLOps/LLMOps/AgentOps, CI/CD, cloud computing, and containerization technologies.
• Excellent communication, collaboration, and problem-solving skills.
• Ability to work independently and in a team environment.
• Passion for innovation and a desire to explore the frontiers of AI to meet business and customer objectives.
• Experience with cloud platforms (Azure, GCP) and their AI/ML services.
• Familiarity with vector/memory stores (e.g., Databricks, Mem0, FAISS, Qdrant, Azure Search).