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Senior/Staff Machine Learning Engineer (Model Dev)

2 hours, 18 minutes ago
United States
Full-time
Lead
Machine Learning Engineer
Software Development
AWS Deep Learning Kubernetes Machine Learning PyTorch TensorFlow
Apply Now
Artera

Artera

Artera specializes in modernizing and enhancing critical infrastructure for energy utilities and municipalities, providing solutions that ensure the reliable distribution and transmission of natural gas and electric power across America.

Construction & Engineering
51-250
View All Jobs 6

Description

  • Lead the technical strategy for patient-facing AI products with product, clinical, biostatistics, and regulatory teams.
  • Design and develop multimodal AI biomarkers using whole-slide images, clinical variables, and molecular data.
  • Advance self-supervised pathology foundation models and downstream architectures for clinical prediction tasks.
  • Ensure biomarker reproducibility across scanners, institutions, staining protocols, and patient populations.
  • Develop mechanistic interpretability methods that explain model decisions and support clinician trust.
  • Build tools and processes for efficient, reproducible, compliant model development, deployment, and monitoring.
  • Author and defend regulatory and quality documentation and represent AI in design and development reviews.
  • Plan multi-quarter programs, manage cross-team dependencies and risks, and deliver submission and launch milestones.
  • Publish research, present at clinical and machine learning venues, and support external collaborations.
  • Mentor machine learning scientists and engineers while promoting scientific rigor, code quality, and clear communication.

Requirements

  • 5+ years of industry experience building deep learning systems with PyTorch or TensorFlow.
  • 2+ years of experience as a technical lead launching and monitoring machine learning products in production.
  • Expertise in oncology and biomarker development, including cancer biology, treatment pathways, clinical endpoints, and risk stratification.
  • Demonstrated ability to scope projects, sequence work, manage dependencies, and deliver dated milestones across teams.
  • Ability to communicate complex machine learning concepts to cross-functional, non-ML collaborators.
  • Experience mentoring or managing machine learning scientists and engineers.
  • Experience applying machine learning to medical imaging, multi-omics, or longitudinal clinical data, including weakly supervised learning, preferred.
  • Experience developing ML in regulated environments, such as FDA 510(k)/De Novo, CE/UKCA, SaMD, design controls, or CLIA/LDT validation, preferred.
  • Experience with self-supervised learning, medical foundation models, clinical cohorts, cloud-scale training, workflow orchestration, and reproducible ML pipelines, preferred.
  • Peer-reviewed publications, conference presentations, or external academic and industry collaborations, preferred.

Interested in this position?

Apply directly on the company website

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