2027 Intern - Machine Learning Engineer

Adobe•San Jose, CA

1d•$45 - $55•Hybrid

About The Position

Adobe is seeking Machine Learning Engineer interns to contribute to impactful AI systems, including generative AI features, intelligent agents, search, recommendations, and production ML models. Interns will work on applied projects with technical teams, potentially building LLM-powered applications, developing multimodal AI systems, designing evaluation frameworks, or deploying models that influence customer experiences with Adobe's creative and marketing products. The internship is a full-time, co-located hybrid role, requiring collaboration between the assigned office and home, with managers determining in-office frequency.

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.
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–September.

Nice To Haves

Familiarity with other languages such as Java or C++.
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.
Exposure to cloud platforms (AWS, Azure, or GCP) or experience with model deployment and evaluation workflows.

Responsibilities

Build and improve machine learning systems, including LLM-based applications, recommendation models, search and retrieval pipelines, or multimodal AI features.
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.