The Role
- You'll work on 5C's computer vision models that analyze millions of medical scans per year. This is an entry-level applied scientist role for someone with strong fundamentals in deep learning and a drive to build models that ship to production.
- You'll work closely with senior scientists and radiologists, learning how to build clinical-grade AI while contributing to real products from day one.
What You'll Work On
- Train and evaluate vision models for medical image classification, detection, and segmentation
- Build data pipelines for curating, cleaning, and augmenting medical imaging datasets
- Run experiments — ablation studies, architecture comparisons, hyperparameter searches — and document findings rigorously
- Help deploy models to production and monitor their performance on live clinical data
- Collaborate with radiologists to understand clinical context and validate model outputs
You Should Have
- 1+ years of experience (or equivalent research/project depth) in deep learning or computer vision
- Strong Python and PyTorch skills — you can write training loops, custom datasets, and model architectures from scratch
- Solid understanding of CNN architectures, vision transformers, and training techniques (augmentation, regularization, mixed-precision)
- Experience with image processing libraries (OpenCV, PIL, scikit-image)
- A GitHub profile or portfolio with code you're proud of
Why 5C
- 5C is one of the best places to work for serious, engaged builders. We are a leading company in agent-driven software development and a leading business in AI for medical imaging — both at the same time
- Small, highly empowered teams. High execution capability, high taste, high agency. No committees, no approval chains — just builders who ship
- Resumes are not important. Proof of work and proof of a high learning rate is everything we look for. Show us what you've built
- Work on models that directly impact patient care. Learn from senior scientists with production medical imaging experience
