ML Engineer Intern: Generative AI & Production ML

Adobe; New York (NY); Hybrid; USD 62,000 - 76,000; Full time

Job summary

Adobe is seeking a Machine Learning Engineer intern to work on impactful AI systems from LLM-powered features to production ML models. You will build, train and deploy models across the ML lifecycle while collaborating with engineers, product managers, and researchers.

Ideal candidates are enrolled full-time in CS/CE with strong ML/DL fundamentals, Python proficiency, and experience with PyTorch or TensorFlow. This is a hybrid internship May–Sept with co-location and team support.

Qualifications

• Enrollment in a full-time degree program with expected graduation Dec 2027–Jun 2028.
• Strong foundation in ML and DL concepts, including generative AI and LLMs.
• Proficiency in Python; Java/C++ familiarity is a plus.
• Experience with ML frameworks PyTorch or TensorFlow; exposure to LLM tooling.
• Cloud platforms (AWS/Azure/GCP) experience is a plus.
• Strong analytical and communication skills.
• Available for a full-time internship May–Sept.

Responsibilities

• Build and improve ML systems including LLM-based apps, recommendation models, search pipelines, or multimodal features.
• Design, train, evaluate, and iterate models across the ML lifecycle from data prep to deployment and monitoring.
• Contribute to applied AI projects with real product impact.
• Collaborate with engineers, PMs, and researchers to scope problems and communicate findings.

Skills

Machine Learning

Deep Learning

Python

Java

C++

PyTorch

TensorFlow

AWS

Azure

GCP

Analytical Thinking

Communication

Education

Bachelor's/Master's/PhD in CS/CE or related

Tools

LLMs tooling (e.g., Hugging Face, LangChain)

Job description

Adobe is seeking a Machine Learning Engineer intern to work on impactful AI systems from LLM-powered features to production ML models. You will build, train and deploy models across the ML lifecycle while collaborating with engineers, product managers, and researchers.

Ideal candidates are enrolled full-time in CS/CE with strong ML/DL fundamentals, Python proficiency, and experience with PyTorch or TensorFlow. This is a hybrid internship May–Sept with co-location and team support.