2027 Machine Learning Engineer Intern

The Opportunity

Adobe is looking for Machine Learning Engineer interns to work on some of the most impactful AI systems in the industry, from generative AI features and intelligent agents to search, recommendations, and production ML models used by hundreds of millions of people.

Depending on your team, you might be building LLM-powered applications, developing multimodal AI systems, designing evaluation frameworks, or deploying models that directly shape how customers experience Adobe's creative and marketing products. The work is applied, the teams are technical, and the projects are real.

All 2027 Adobe interns will be co-located hybrid, working between their assigned office and home, based where their manager and team are located. This will allow you to get the most support to ensure collaboration and the best employee experience. Managers will determine the frequency you need to go into the office to meet priorities.

What You'll Do

• Build and improve machine learning systems, including LLM-based applications, recommendation models, search and retrieval pipelines, or multimodal AI features, depending on your team's focus.
• Design, train, evaluate, and iterate on models across the full ML lifecycle, from data preparation and experimentation through deployment and monitoring in production environments.
• Contribute to applied AI projects with real product impact, including generative AI features, agentic workflows, and intelligent systems used by Adobe customers at scale.
• Collaborate closely with engineers, product managers, and researchers to scope problems, ship working solutions, and communicate findings to both technical and non-technical stakeholders.

What You Need to Succeed

• Currently enrolled full time and pursuing a Bachelor's, Master's, or PhD degree in Computer Science, Computer Engineering, or a related technical field, with an expected graduation date of December 2027 to June 2028.
• Strong foundation in machine learning and deep learning concepts, including familiarity with generative AI and large language models (LLMs).
• Strong Python programming skills; familiarity with other languages such as Java or C++ is a plus.
• Hands-on experience with machine learning frameworks such as PyTorch or TensorFlow; familiarity with LLM tooling (e.g., Hugging Face, LangChain) or ML libraries such as scikit-learn is a plus.
• Exposure to cloud platforms (AWS, Azure, or GCP) or experience with model deployment and evaluation workflows is a plus.
• Strong analytical and quantitative problem-solving ability.
• Excellent communication skills and ability to work effectively in a collaborative team environment.
• Ability to participate in a full-time internship between May and September.