2025 Intern - Data Scientist, Firefly

The Opportunity  

Firefly is the family of creative generative AI models integrated with most Adobe products that offers a new way to conceptualize, build, and scale content. It’s a natural extension of the technology Adobe has produced over the past 40 years. At the core of Firefly are our commercially safe AI models trained on hundreds of millions of contents (e.g., images, videos) owned or licensed by Adobe. 

The Adobe Firefly Data Science team is looking for summer interns. The team applies AI and machine learning techniques to big customer data to address and challenge business problems, such as driving go-to-market strategies, sales prioritization, increasing product engagement and customer service improvement. 

All 2025 Adobe interns will be co-located hybrid. This means that interns will work between their assigned office and home. Interns will be based in the office where their manager and/or team are located, where they will get the most support to ensure collaboration and the best employee experience. Managers and their organization will determine the frequency they need to go into the office to meet priorities.   

What You’ll Do 

• Apply data mining, machine learning, and NLP to real-world problems and datasets 

• Analyze massive data sets using statistical techniques to generate insights and make predictions 

• Develop machine learning models at scale from conceptualization to business impact 

• Extract and analyze data to understand the customer product life cycle and value realization from the product 

What You Need to Succeed  

• Currently enrolled full time and pursuing a Master’s or PhD degree in Computer Science, Data Science, Information Science, Statistics, Applied Mathematics, or Engineering is desired; with an expected graduation date of December 2025 – June 2026  

• Solid understanding of SQL and Python 

• Solid understanding of machine learning/data mining/statistical modeling concepts, and a track record solving problems with these methods 

• Ability to apply machine learning/statistical techniques such as supervised/unsupervised learning, NLP techniques, LLM, time series forecasting, explainable AI, reinforcement learning, A/B testing, causal etc. 

• Ability to work on modern data science workflows on the cloud, and ML frameworks. (Git, Jupyter Notebook, Azure, AWS, Databricks, Spark-SQL, Airflow) 

• Ability to participate in a full-time internship between May-September 2025