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Machine Learning Intern (Summer 2026)
ArteraRemote-US, United StatesRemoteinternshipVerifiedPosted 5 Dec 2025
About the role
About Us: Artera is an AI startup that develops medical artificial intelligence tests to personalize therapy for cancer patients. Artera is on a mission to personalize medical decisions for patients and physicians on a global scale.
As a Machine Learning Intern at Artera, you will work with a team of machine learning practitioners to develop AI-based biomarkers to support the personalization of cancer therapy. Using digital imagery and clinical data you will design multi-modal computer vision and deep learning models that can prognosticate patient outcomes and predict response to therapy.
As a Machine Learning Intern at Artera, you will work with a team of machine learning practitioners to develop AI-based biomarkers to support the personalization of cancer therapy. Using digital imagery and clinical data you will design multi-modal computer vision and deep learning models that can prognosticate patient outcomes and predict response to therapy.
Essential Responsibilities:
- Developing novel biomarkers alongside fellow ML engineers, biostatisticians, and scientific directors
- Design and develop innovative computer vision models that predict patient outcomes and responses to therapy
- Support and optimize our machine learning workflow by enhancing the efficiency of tools, processes, and systems used to develop and deploy AI-based biomarkers
- Aid in the productionalization, launch, and monitoring of machine learning products
- Research and development of machine learning algorithms that expand product capabilities
- Contribute to and drive publications in scientific journals and machine learning conferences
Education and Experience Requirements:
- 2+ years of academic or industry experience using PyTorch or TensorFlow
- Ability to communicate technical (ML) details to a cross-functional team of non-technical collaborators.
- Entering the final year of Masters or Phd following the summer of 2026
- (Preferred but not required) Hands-on experience with vision-language models (VLMs), including training, fine-tuning, or evaluating multimodal models
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