Principal Machine Learning Engineer (Reconstruction / Quantitative Imaging)
Core
Build ML components for medical image reconstruction to improve quality, speed, robustness, and quantitative accuracy.
Role type
Principal Machine Learning Engineer (Reconstruction / Quantitative Imaging)
Builds
Medical imaging reconstruction pipelines and hybrid physics-ML algorithms
Domain
Medical Imaging / Physics-based Inverse Problems
Deliverable
production ML models
Required skills
Applied ML, Signal Processing, Imaging, GPU optimization, Physics-based modeling, Data curation, Model evaluation, Reproducibility, Hybrid algorithm design
Preferred skills
PiNNs, Neural Operators, PDE solving, Agentic-SciML, Data assimilation, Kalman filtering, Variational methods
Technologies
GPU, PiNNs, Neural Operators
Responsibilities
Partner with scientists to build ML components for reconstruction; Define training/evaluation pipelines and metrics; Productionize models with monitoring and safe fallbacks; Collaborate on hybrid algorithms combining physics and learned priors; Build tooling for rapid experimentation and verification.
Seniority
Principal, hands-on IC with strategy & mentorship
