2027 Intern - Machine Learning Engineer

About the role

Adobe seeks Machine Learning Engineer interns to develop impactful AI systems. These cover creative AI, intelligent agents, search, recommendations, and production ML models used by millions. Based on your team, you might be building LLM-powered applications or developing multimodal AI systems. You could also compose evaluation frameworks or deploy models that directly influence how customers experience Adobe's creative and marketing products.

Responsibilities

• 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 partners

Requirements

• 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 – 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