Machine Learning Scientist – Digital Pathology & Multimodal AI

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Boston Gene is redefining precision medicine with its AI-powered, multiomic approach to understanding and treating complex diseases. By integrating deep molecular profiling—including genomics, proteomics and the immune system—the platform delivers a systems biology view that accelerates drug development and clinical decision-making. With a CLIA-certified, CAP-accredited lab, Boston Gene provides clinically validated insights that personalize care and support translational breakthroughs. Partnering with leading pharma, biotech and cancer centers, Boston Gene drives innovation and advances transformative therapies.

Position Summary

We are seeking a Machine Learning Scientist to join our Digital Pathology Data Science team. This role will focus on developing and deploying AI models for whole-slide images (WSIs), and integrating these insights with molecular and clinical data. You will work closely with a multidisciplinary team to advance biomarker discovery, therapeutic development, and real-world clinical applications.

Key Responsibilities

• Model Development: Design, train, and validate deep learning models for pathology image analysis, including tasks such as tissue classification, cellular segmentation, and spatial biomarker prediction.
• Multimodal Integration: Collaborate on AI models that fuse digital pathology data with genomic, transcriptomic, and clinical modalities.
• Algorithm Validation & Deployment: Conduct analytical and clinical validation of models and deploy them in research and production environments.
• Data Management & Curation: Work with large-scale histopathology datasets, including WSI annotation, image preprocessing, and data quality assurance.
• Collaborative Research: Partner with pathologists, computational biologists, immunologists, and software engineers to ensure model outputs are biologically and clinically meaningful.
• Innovation & Publication: Contribute to internal R&D initiatives, stay up to date with the latest ML research in medical imaging, and support scientific publications and presentations.
• Biomarker Discovery: Help identify spatial and morphological features associated with patient outcomes and therapeutic responses.

Required Qualifications

• PhD (or MS with 2+ years experience) in Computer Science, Artificial Intelligence, Computational Biology, or related field.
• Strong experience with deep learning architectures (CNNs, ViTs, UNet, etc.) for image classification, segmentation, or detection.
• Solid understanding of machine learning principles including self-supervised and weakly supervised learning.
• Proficiency in Python and deep learning frameworks such as PyTorch or Tensor Flow.
• Experience working with whole-slide images and digital pathology datasets.
• Strong problem-solving and communication skills; ability to work in cross-functional teams.
• Demonstrated contributions through publications, patents, or production-level ML applications.

Preferred Qualifications

• Experience with pretraining or fine-tuning of foundational or multimodal models.
• Familiarity with spatial omics, RNA/DNA sequencing, or clinical datasets.
• Background in oncology, immunology, or precision diagnostics.
• Industry experience in biotech, healthcare, or regulated environments.

What We Offer

• Opportunity to shape foundational AI models that impact patient care
• Access to rich multimodal datasets and clinical collaborations
• A collaborative, mission-driven culture focused on innovation
• Competitive salary, stock options, and comprehensive benefits

• Seniority level
  
  Mid-Senior level

• Employment type
  
  Full-time

• Job function
  
  Science and Information Technology
• Industries Biotechnology, Biotechnology Research, and Pharmaceutical Manufacturing

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Medical insurance

Vision insurance

401(k)

Paid maternity leave

Paid paternity leave

Tuition assistance

Disability insurance

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