Machine Learning Engineer for Medical Image Analysis

Barrington James • United State
Remote
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AI Summary

We are seeking a Machine Learning Engineer to design, train, and deploy deep learning models for large-scale medical image analysis. This is a hands-on role focused on taking models from experimentation through production in a regulated, high-impact environment. The ideal candidate will have 3+ years of experience in machine learning or applied AI.

Key Highlights
Design, train, and deploy deep learning models for medical image analysis
Collaborate with engineering teams to deploy models into production
Improve model performance, robustness, and generalization
Key Responsibilities
Build and train deep learning models for medical image analysis
Develop and maintain ML pipelines for training, evaluation, and inference
Collaborate with engineering teams to deploy models into production
Technical Skills Required
Python PyTorch TensorFlow Deep learning architectures Cloud environments MLOps
Benefits & Perks
Fully remote role with a high level of autonomy
Competitive compensation and equity
Opportunity to grow alongside a scaling AI healthcare company
Nice to Have
Experience with medical imaging, digital pathology, or healthcare data
Exposure to MLOps, model deployment, or production ML systems
Prior experience in regulated industries (healthcare, life sciences, diagnostics)

Job Description


Our client is a venture-backed healthcare AI company building advanced machine learning systems to extract clinically meaningful insights from medical images. Their platform applies deep learning to real-world pathology data to support disease risk stratification, treatment decision-making, and precision medicine initiatives across clinical and research settings.

The team operates at the intersection of machine learning, medical imaging, and healthcare delivery, with technology already being used in real clinical workflows.


The Role

We are seeking a Machine Learning Engineer with 3+ years of experience to help design, train, and deploy deep learning models for large-scale medical image analysis. This is a hands-on role focused on taking models from experimentation through production in a regulated, high-impact environment.


You’ll work closely with ML researchers, software engineers, and domain experts to build scalable ML systems that directly support patient care and life sciences research.


Key Responsibilities

  • Build and train deep learning models for medical image analysis
  • Work with large image datasets and associated clinical metadata
  • Develop and maintain ML pipelines for training, evaluation, and inference
  • Collaborate with engineering teams to deploy models into production
  • Improve model performance, robustness, and generalization
  • Contribute to ML best practices including validation, monitoring, and reproducibility
  • Participate in cross-functional collaboration with product and clinical stakeholders


Required Qualifications

  • 3+ years of professional experience in machine learning or applied AI
  • Strong Python skills and experience with PyTorch and/or TensorFlow
  • Solid foundation in deep learning architectures and training methodologies
  • Experience working with image data (medical imaging experience is a plus, not required)
  • Familiarity with cloud environments and modern ML workflows
  • Comfortable working in a fully remote, collaborative team


Preferred / Nice to Have

  • Experience with medical imaging, digital pathology, or healthcare data
  • Exposure to MLOps, model deployment, or production ML systems
  • Prior experience in regulated industries (healthcare, life sciences, diagnostics)


Why This Opportunity

  • Fully remote role with a high level of autonomy
  • Work on production ML systems with real clinical impact
  • Highly technical, collaborative team environment
  • Competitive compensation and equity
  • Opportunity to grow alongside a scaling AI healthcare company


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