AI/ML Intern, Computer Vision

Johnson & Johnson • San Diego, CA

19h • $23 - $59

About The Position

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 https://www.jnj.com/innovative-medicine About the role We are seeking a motivated research intern to contribute to foundational R&D for large-scale, multi-modal visual models applied to medical and clinical imaging. The role focuses on three broad, generic research areas: (1) modular model architectures that enable specialization and efficiency through multiple subcomponents, (2) predictive and alignment-based approaches that improve contextual and temporal understanding across images and videos, and (3) improvements to representation-learning pipelines that make better use of unlabeled data and modality-specific preprocessing. Projects will involve medical imaging modalities such as histopathology, X-rays, endoscopy video, and dermatology imaging.

Requirements

• Currently pursuing or recently completed a Bachelor’s, Master’s, or PhD in Computer Science, Engineering, Applied Mathematics, or a related field.
• Strong programming ability (Python) and experience with common machine learning libraries.
• Solid understanding of machine learning and computer vision fundamentals and of how to train and evaluate models.
• Experience running experiments, tracking results, and performing basic troubleshooting and analysis.
• Strong written and verbal communication skills.
• Permanently authorized to work in the U.S., must not require sponsorship of an employment visa (e.g., H-1B or green card) at the time of application or in the future.
• Students currently on CPT, OPT, or STEM OPT usually requires future sponsorship for long term employment and do not meet the requirements for this program unless eligible for an alternative long-term status that does not require company sponsorship.

Nice To Haves

• Prior research or project experience related to modular model design, predictive/alignment methods for representation learning, or representation learning using unlabeled data.
• Experience working with medical imaging or multi-modal visual data (including video) and familiarity with common preprocessing challenges.
• Experience with training models at scale and with experiment management practices.
• Understanding of clinical evaluation metrics and concerns around generalization and robustness in medical imaging.
• Publications, open-source contributions, or a portfolio demonstrating relevant work.

Responsibilities

• Design, implement, and evaluate scalable modular model architectures that allow specialization and efficient use of computation.
• Develop and test methods that learn richer contextual and temporal representations by predicting or aligning different views, frames, or modalities.
• Improve representation-learning pipelines by experimenting with data preparation strategies, augmentation approaches, training schedules, and hyperparameter settings to increase robustness across modalities.
• Build reproducible training and evaluation workflows and run experiments at scale; maintain clear experiment logs and analyses.
• Measure model effectiveness on clinically relevant downstream tasks (e.g., classification, detection, segmentation, retrieval, temporal reasoning) and produce comparison reports and ablation studies.
• Collaborate with data engineers, clinicians, and researchers to curate and prepare datasets while following privacy and governance requirements.
• Produce well-documented code, experiment artifacts, internal reports, and, where appropriate, contribute to technical write-ups or presentations.

Benefits

• Co-Ops/Interns are eligible to participate in Company sponsored employee medical benefits in accordance with the terms of the plan.
• Co-Ops and Interns are eligible for the following sick time benefits: up to 40 hours per calendar year; for employees who reside in the State of Washington, up to 56 hours per calendar year.
• Co-Ops and Interns are eligible to participate in the Company’s consolidated retirement plan (pension).

What This Job Offers

• Career Level: Intern