Jobs at Djinni

We are looking for a Community Manager to handle public comments for our brand across Facebook, Instagram, and X. The primary goal is to maintain an engaging dialogue with the audience, build brand trust, handle negative feedback professionally, and guide users to the support team for the resolution of specific issues.

Who we are looking for:

• High level of written English and the ability to use ChatGPT to draft responses in Pan-African English and French;
• Ability to review and edit ChatGPT-generated responses: correcting unnatural phrasing, accounting for local context, and verifying facts;
• Understanding of online community dynamics;
• Ability to handle complaints, criticism, and provocations calmly—without engaging in arguments, assigning blame, or using sarcasm;
• Ability to determine which questions can be answered publicly and which need to be moved to private messages for further handling by the support team.;
• Ability to categorize inquiries and hand them over with sufficient context and a clear next step;
• Adherence to confidentiality: protecting users' personal data and not disclosing internal processes or details regarding checks.

• Communicate on behalf of the brand in comments and communities across Facebook, Instagram, and X, adapting the tone of voice to the specific channel and situation;
• Monitor comments while taking the post's context into account;
• Propose appropriate, timely responses to comments and events, incorporating local humor and cultural context;
• Handle negative comments without engaging in arguments or aggressively defending the brand;
• Moderate spam, bots, suspicious links, and provocations; remove harmful or spam comments via social media management tools in accordance with established guidelines;
• Escalate complex moderation cases, negative discussions gaining significant reach, and other reputation-related risks to the team lead;
• Manage the comment queue in Front: categorize inquiries and apply the correct tags;
• Coordinate complex responses with the support team, verify case acceptance, and communicate clear next steps to the player;
• Work with the content schedule: stay up to date on post topics, FAQs, and approved links;
• Use ChatGPT to draft and localize responses, ensuring accuracy, natural phrasing, and appropriateness;
• Monitor community sentiment and provide the team lead with structured feedback regarding recurring user issues;
• Observe the rules safe communication: do not discuss personal data publicly, do not disclose internal processes, and do not promise compensation or timelines without confirmation from the responsible team.

• Good understanding of various sports, especially football: familiarity with terminology, clubs, players, tournaments, favorites, and current events;
• Experience in community management or moderating online communities/social media channels;
• Knowledge of French;
• Experience working with Front or similar helpdesk systems.

• Stable schedule and remote work;
• Support from Team Lead on various tasks;
• 20 working-days paid annual leave, 5 days paid sick leave, UA national holidays;
• High salary growth potential;
• Competitive compensation depending on success of your work and your results;
• A unique work environment where you can be a part of creating a new and innovative product.

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?