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Intern Ai Data Annotation Jobs in Indiana (NOW HIRING)

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Intern Ai Data Annotation information

What are the key skills and qualifications needed to thrive as an Intern AI Data Annotation Specialist, and why are they important?

To thrive as an Intern AI Data Annotation Specialist, you need strong attention to detail, basic data handling skills, and familiarity with common data formats, often supported by a background in computer science or related fields. Experience with data labeling tools, annotation platforms, and sometimes basic knowledge of Python or similar scripting languages is typically required. Reliability, patience, and effective communication are essential soft skills for ensuring accuracy and collaborating with team members. These competencies are crucial for generating high-quality annotated datasets that enable accurate machine learning model development.

What does a typical day look like for an AI Data Annotation Intern, and how do they collaborate with other teams?

As an AI Data Annotation Intern, your typical day involves labeling and categorizing data such as images, audio, or text to train machine learning models. You’ll use specialized annotation tools and follow detailed guidelines to ensure consistency and accuracy. Collaboration is key—you’ll often communicate with data scientists, machine learning engineers, and project managers to clarify requirements and provide feedback on ambiguous cases. This teamwork helps ensure the data you annotate aligns with project goals and quality standards, making your contributions vital to the development of AI solutions.

What does an Intern AI Data Annotation do?

An Intern AI Data Annotation is responsible for labeling and categorizing data, such as images, text, or audio, to help train artificial intelligence models. They ensure data is accurately tagged according to specific guidelines so that AI systems can learn to recognize patterns or make predictions. This role often involves using specialized annotation tools and requires attention to detail to maintain high-quality datasets. Interns may also assist with reviewing and correcting data, as well as collaborating with data scientists and engineers to improve annotation processes.
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Research Scientist Intern (2025)

Research Scientist Intern (2025)

Whiterabbit.ai

South Bend, IN • On-site

Other

Posted 18 days ago


Job description

We are looking for a Research Scientist Intern to push the state of the art of our AI models. As a Research Scientist Intern at Whiterabbit.ai, you will:

  • Play a key role in architecting the algorithms and models that will power our products
  • Train on a dedicated high-performance compute cluster specialized for deep learning research
  • Work with doctors and healthcare professionals to identify serious problems and leverage their domain expertise to build robust solutions
  • Remain an active contributor to the research community by partnering with universities and publishing high impact papers

Who we are:

Our mission at Whiterabbit.ai is to save lives and eliminate suffering through the early detection of cancer with artificial intelligence. We collaborate closely with one of the top medical schools in the country and have exclusive access to one of the world’s largest cancer datasets with millions of images. We invent algorithms that make doctors more productive, more accurate, and more capable. We build products and services with a relentless focus on transforming the patient’s healthcare experience.

Responsibilities

  • Develop highly scalable classifiers and detectors that solve real-world problems
  • Learn and understand a large body of research in deep learning and machine learning
  • Participate in cutting-edge research for medical applications of computer vision

Must Have Experience

  • Experience with deep learning and convolutional networks
  • Strong theoretical and empirical research background
  • Fluency with a deep learning framework and Python

Nice to Have Experience

  • Contributions to research communities and efforts, such as publications at conferences like CVPR, NeurIPS, ICCV, ECCV, ICML, and ICLR
  • Large scale machine learning experience working with terabytes of data
  • Implemented custom operations/modules in a deep learning framework
  • Imagination, ambition, and curiosity