GenAI Engineer​/Eval Engineer Summer Internship

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and Med Tech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn

more at

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function:

Career Programs

Job Sub Function:

Non-LDP Intern/Co-Op

Job Category:

Career Program

All Job Posting Locations:

San Diego, California, United States of America, Titusville, New Jersey, United States of America

Job Description:

About Innovative Medicine

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

Learn more at

We are searching for the best talent for GenAI/ Eval Engineers (3 Positions) based in any of the locations (Titusville, NJ/Raritan, NJ/La Jolla, CA/Hybrid)

Purpose:

We are seeking a highly motivated GenAI/ EVAL Engineer Intern to join our AI/ML team within the Innovative Medicine division. This internship provides a valuable opportunity for college juniors and seniors passionate about applied machine learning and data engineering.

In this role, you will contribute to real-world projects focused on transforming healthcare through generative AI and data solutions. You'll collaborate with data scientists and engineers to develop, optimize, and deploy machine learning models, building scalable ML pipelines that support critical business objectives.

You will be responsible for :

* Use hands-on exploration to gain exposure to and familiarity with large-scale datasets, including text, images, and structured data

* Build data engineering pipelines to transform and enrich datasets for generative AI model training and evaluation

* Develop backend cloud engineering infrastructure that enables scalable AI/ML deployment and automation frameworks

* Stay informed on cutting-edge applications and tools in generative AI, AI Operations, and cloud computing , and present insights to the team through trainings and discussions

* Develop code-based automated data pipelines capable of processing large volumes of multimodal data for AI applications

* Contribute to the design and implementation of AI Agents and authoring tools that enable smarter, more efficient content creation and management processes.

Qualifications / Requirements:

Required:

* Currently pursuing a degree in Computer Science, Data Science, Bioinformatics, Engineering, Digital Health, or a related field.

* Strong understanding of core concepts in Statistics, Data Science, or Computer Science, as demonstrated through current or prior coursework.

* Excellent written and verbal communication skills, with the ability to convey technical and non-technical concepts effectively.

* Familiarity with exploring and analyzing large datasets.

* A genuine interest in innovative research in Digital Health and Real World Data, along with a desire to gain domain knowledge in the field.

* Experience with Git version control and writing code in Python

Preferred:

* Background or coursework in computer science, information systems, biomedical engineering, or life sciences.

* Hands-on experience through internships or projects involving data engineering and data science.

* Familiarity with machine learning frameworks (e.g., Tensor Flow, PyTorch, Hugging Face), Dev Ops tools (e.g Jenkins, Docker, Kubeflow, Sage Maker).

* Experience with cloud platforms (AWS, GCP, Azure) and…