PstrongAbout Amplifier AI /strong /ppbr / /ppWe're building the next generation of surgical planning software for interventional radiology and cardiothoracic surgery.
Our platform turns CT scans into interactive 3D models that help surgeons plan complex procedures — from endovascular aortic repair (EVAR) to transcatheter aortic valve implantation (TAVI) and beyond.
/ppOur core library powers 17+ clinical analysis pipelines that perform automated anatomical segmentation, vessel centerline extraction, hemodynamic measurements, and risk stratification.
Every algorithm we ship has a direct impact on patient outcomes.
/ppWe're a small, focused team where your code goes from PR to operating-room screen in weeks, not quarters.
If you want to work on technically challenging problems that genuinely matter, keep reading.
/ppbr / /ppstrongWhat You'll Work On /strong /ppstrongThis isn't a generic backend role.
Here's what a typical month might look like: /strong /pulliExtending our NNUnet-based segmentation pipelines (we run 15+ trained models across organs, vessels, bones, and tumors) and validating results against clinical ground truth /liliBuilding automated measurement workflows — think aortic neck angulation, iliac tortuosity indices, or landing-zone diameter calculations that feed directly into surgical reports /liliDeveloping new workspace modules: designing the data flow from raw DICOM volumes through preprocessing, AI inference, post-processing, and 3D scene generation /liliOptimizing inference performance for GPU and CPU execution, including memory-aware scheduling and adaptive resolution strategies /liliWorking with SimpleITK, NumPy, and our in-house volume processing library to manipulate medical images at the voxel level — resampling, label morphology, island filtering, ROI extraction /liliCollaborating directly with radiologists and surgeons to translate clinical requirements into algorithmic specifications /li /ulpstrongOur Tech Stack /strong /pulliLanguage: Python 3.12+ (modern typing, dataclasses, async patterns) /liliMedical Imaging: SimpleITK, NIfTI volumes, DICOM processing /liliAI/ML: NNUnet framework, PyTorch, custom inference pipelines /liliInfrastructure: Docker, NVIDIA GPU compute, CI/CD with automated testing /lili3D Visualization: Unity integration (you won't write C#, but your Python outputs drive the 3D viewer) /liliTools: Git, Jira, Confluence, VS Code / PyCharm /li /ulpbr / /ppstrongWhat We're Looking For /strong /ppstrongMust-haves: /strong /pulliStrong Python fundamentals: you write clean, typed, well-structured code and understand performance trade-offs /liliExperience with NumPy/SciPy for numerical computing — you're comfortable thinking in arrays and transforms /liliFamiliarity with medical imaging concepts (DICOM, NIfTI, voxel spaces, coordinate systems) or strong willingness to learn quickly /liliUnderstanding of machine learning inference pipelines, even if you're not training models from scratch /liliAbility to work independently in a remote-first environment with 4+ hours of overlap with CET business hours /li /ulpstrongNice-to-haves: /strong /pulliExperience with SimpleITK or ITK for image registration, segmentation, or morphological operations /liliBackground in NNUnet or similar medical segmentation frameworks /liliKnowledge of 3D geometry: meshes, centerline extraction, spatial transforms /liliContributions to open-source scientific Python projects /liliDomain experience in radiology, surgical planning, or health-tech /li /ulpbr / /ppstrong A Few Things to Know /strong /pulliThe codebase is scientifically dense — you'll work with Hounsfield units, anatomical coordinate systems, and clinical measurement standards.
Curiosity about the domain is essential.
/liliWe're a startup.
Processes are evolving, requirements shift, and you'll sometimes need to figure things out from first principles rather than following established playbooks.
/liliThis is primarily a backend/algorithmic role.
If you're looking for frontend or web development work, this isn't the right fit.
/liliWe care deeply about code quality — type hints, meaningful tests, clear documentation.
We review each other's work carefully.
/li /ulpbr / /ppstrongWhy Join Us /strong /pulliDirect clinical impact: your code helps surgeons plan life-saving procedures more accurately /liliTechnically deep work at the intersection of AI, medical imaging, and 3D visualization /liliSmall team, big ownership: you'll shape architecture decisions and see your ideas go to production /liliFlexible remote setup with asynchronous communication and minimal meetings /liliCompetitive compensation with equity participation /li /ulpbr / /ppstrongHow to Apply /strong /ppstrongSend us your CV along with a short note covering: /strong /polliA brief description of the most technically challenging Python project you've worked on — what made it hard, and how you solved it.
/liliYour experience (if any) with medical imaging, numerical computing, or ML inference — even if it's from a different domain.
/liliYour availability and time zone.
/li /olulliNo cover letter template needed — just be direct.
We review every application personally.
/li /ul