Machine Learning Engineer
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Job Description
Machine Learning Engineer developing AI-based biomarkers utilizing multimodal deep-learning models to personalize cancer therapy. Collaborating with cross-functional teams on model development and deployment.
Responsibilities:
- Help develop AI-based biomarkers that support the personalization of cancer therapy.
- Work on multimodal deep-learning models that integrate large-scale pathology whole-slide images with diverse modalities to predict patient risk and response to therapy.
- Contribute to developing robust, scalable solutions in this space.
- Collaborate closely with fellow ML engineers, biostatisticians, scientific directors, and product partners to build, validate, and deploy models that ultimately impact patient care.
Requirements:
- 2+ years of industry experience using PyTorch or TensorFlow.
- Experience contributing to machine-learning systems deployed or maintained in production environments.
- Ability to clearly communicate complex technical concepts to cross-functional, non-ML collaborators.
- Experience working with large-scale image data or computer vision models.
- Familiarity with self-supervised representation learning (e.g., MoCo, DINOv2) and / or vision–language models (VLMs) and multimodal representation learning.
- Interest in healthcare, medical imaging, or applied machine learning in regulated or high-impact domains.
Benefits:
- 401k matching
- Unlimited paid time off (PTO)
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