Clinical CV & ML Ops Engineer for AR Imaging

StellDirVor GmbH; United States; Hybrid; USD 84,000 - 123,000; Full time

Benefits offered by this job

Remote-friendly setup

Learning budget

Munich office option

Job summary

StellDirVor GmbH is developing ARAIAS, an AR‑and AI‑based hands‑free training system for chronic wound care. You will build core AI capabilities, evaluate computer vision models on smart glasses data, and manage ML operations from data gathering to deployment.

The role welcomes candidates at different levels with a solid ML foundation in medical imaging and a pragmatic, autonomous approach. The position offers a hybrid work setup, with opportunities to contribute to cutting‑edge education and

Qualifications

• Solid ML background with computer vision and ML Ops awareness.
• Strong Python skills and hands-on PyTorch, OpenCV or TensorFlow experience.
• Experience with transfer learning and full ML lifecycle, from data to deployment.
• Familiarity with medical imaging challenges and data privacy considerations.
• Ability to read research papers and apply findings pragmatically.

Responsibilities

• Select and benchmark pre-trained models for medical image analysis and adapt to domain data.
• Develop generative AI models to create realistic synthetic medical images for education.
• Evaluate and fine-tune small language models for on-device speech and interactions.
• Plan the ML ops pipeline: data gathering, annotation, preparation, training, testing and deployment.
• Estimate compute costs and compare build vs. buy options to support budgeting.
• Document data sources, experiments and design decisions for audits.

Skills

Python

PyTorch

OpenCV

TensorFlow

Transfer learning

ML lifecycle

Medical imaging

English fluency

Education

Degree in Computer Science, Data Science, Biomedical Engineering, Mathematics or related field

Tools

Docker

MLflow

Weights & Biases

DVC

ONNX

Job description

StellDirVor GmbH is developing ARAIAS, an AR‑and AI‑based hands‑free training system for chronic wound care. You will build core AI capabilities, evaluate computer vision models on smart glasses data, and manage ML operations from data gathering to deployment.

The role welcomes candidates at different levels with a solid ML foundation in medical imaging and a pragmatic, autonomous approach. The position offers a hybrid work setup, with opportunities to contribute to cutting‑edge education and