Python Developer Medical Imaging (3-D Reconstruction - Measurement)

Job description

Amplifier AI is building a surgical planning

platform powered by our own imaging,

segmentation and 3-D measurement engine.

We are a small team of engineers, radiologists

and data scientists from Ukraine and across

Europe. You would join the team developing the

internal Python engine behind 3-D

reconstruction and measurement for CT-based

workflows.

Read this before you apply

We hire for reasoning about 3-D space, not

for a title. The code itself is ordinary clean

Python — the hard part is everything the

geometry touches:

Voxel space vs. physical space, and every

transform between them

Origin, spacing and direction — consistent

across scanners, series and vendors

Real hospital data: incomplete series, odd

orientations, inconsistent metadata

Geometric edge cases — surfaces that self-

intersect, clips that miss, distances that are

"almost" right

Reproducibility: the same input must give the

same number, today and in six months

If you can explain why a model is offset,

mirrored or at the wrong scale — not just that it

looks wrong — you will do well here.

Because the output feeds real surgical planning,

correctness is not negotiable. A wrong

millimetre is a clinical problem, not a bug report.

This role is probably not for you if you want

fully predefined tickets, a fixed roadmap, or to

implement tasks without understanding the

domain. Hospitals and real clinical data change

priorities; we adjust as a team.

What We're Looking For

Python engineering (the core of this role)

- Clean, modular, strictly typed Python. We run

mypy --strict, ruff, pytest, pre-

commit — and deep, technical code reviews.

- Confident with NumPy / SciPy and array-

heavy numerical code.

- Ability to own a feature end-to-end: from

understanding the clinical problem to

validating the result on real data.

3-D medical imaging fundamentals

-Understanding of origin, spacing and

direction, and the difference between voxel

and physical coordinates.

-Reading DICOM series correctly, validating

RAS orientation, resampling without silently

corrupting geometry.

-Comfort debugging complex geometric

problems: distance, intersection, clipping,

surface generation from labels.

Toolchain

-SimpleITK, VTK or PyTorch experience is a

strong plus. If you haven't used them, you

must be genuinely comfortable diving deep

and learning independently — we mentor, but

initiative is expected.

-Docker, Git, GitHub Actions, structured

logging.

Ways of working

-Clear technical communication — you can

explain your reasoning and defend a design.

-Ownership over micromanagement. Good

written and spoken English.

What You'll Do

- DICOM & SimpleITK: read series correctly,

validate RAS origins and directions, resample

safely, maintain voxel ↔ physical transforms.

- VTK & geometry: generate surfaces from

labels; implement distance, intersection and

clipping algorithms; export reliable STL

markers and geometry artifacts.

- Measurement & QA logic: build robust

procedural tools for radiologists and handle

the edge cases real hospital data produces.

- Pipeline reliability: performance tuning,

structured logging, and making sure

pipelines survive messy multi-scanner

datasets.

Example challenges

- Build a robust distance-measurement tool

between anatomical segmentations, with

exportable nearest-point markers.

- Extract centerlines and anatomical landmarks

from noisy CT scans.

- Enforce consistent spacing / origin / direction

across multi-scanner datasets.

If these sound exciting rather than

overwhelming, you'll likely enjoy this role.

Nice to Have

- VTK surface / volume rendering experience.

- ML segmentation metrics and tooling (Dice,

Hausdorff, nnU-Net, PyTorch).

- GPU acceleration and large-volume

performance work.

- Background in radiology, biomedical

engineering or clinical imaging.

Our Stack

Python 3.13+ · SimpleITK · VTK · NumPy / SciPy

· Pydantic · PyTorch · nnU-Net · pytest · mypy

(strict) · ruff · pre-commit · Docker · GitHub

Actions · Git LFS · Sentry

What We Offer

Competitive salary, optional stock options, and

a clear path toward senior-level ownership and

technical lead responsibilities. Fully remote,

small team, no corporate theater.

How to Apply

- CV or LinkedIn

- GitHub or portfolio — we value real code

- A short note: why does working in an

evolving product environment excite you?