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Machine learning engineer (computer vision)
Swiss Biotech Association —Basel, BS
- Homeoffice
- Doktorat
- Englisch
- Kommunikationsfähigkeit
PI Data Historian, Integration System Engineer (a) 80 - 100%
Bachem Holding AG —Stein AG, AG
- Homeoffice
- Englisch
- Forschungserfahrung
- Analysefähigkeit
- Pensionskasse

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PI Data Historian, Integration System Engineer (a) 80 - 100%
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Machine learning engineer (computer vision)

Swiss Biotech Association
Basel, BS

Jetzt bewerben

Details zur Stelle

Qualifikationen

Doktorat
Git
Englisch
Verpackung
Kommunikationsfähigkeit
Python

Vollständige Stellenbeschreibung

Moonlight AI is transforming clinical diagnostics by extracting genomic information from routine microscopic imaging. Our diagnostics platform leverages routine imaging of hematology and cytology smears to detect genomic biomarkers and diagnose complex diseases. Moonlight AI's goal is to make diagnostics faster, more scalable, and more accessible, supporting diagnostic labs with tools they can trust in real-world settings. We’re a focused team working at the intersection of machine learning, medical imaging, and clinical infrastructure, and we’re looking for people who care deeply about building a better future for patients.

The Machine Learning Engineer will lead the development of the core algorithms powering Moonlight’s AI platform. This high-impact role drives execution of the R&D roadmap, sitting at the intersection of computer vision, engineering, and product development.

Responsibilities:

Develop, validate, and document deep learning algorithms to extract molecular results from whole slide images
Lead experimentation to build novel algorithms: define hypotheses, execute experiments, and iterate while protecting the critical path
Collaborate closely with clinical, product, and business functions to translate requirements into model specifications
Partner with data engineering to build scalable pipelines for data processing, traceability, and compliance
Contribute to building Moonlight’s AI platform, including model integration, performance optimization, and deployment workflows
Develop explainability and interpretability methods to support clinical trust and validation
Generate clinical validation evidence to support regulatory submissions and go-to-market efforts

Requirements:

PhD in Computer Vision, Biomedical Image Analysis, or a related field
Fluent in Python and at least one deep learning framework (e.g., PyTorch, TensorFlow)
4+ years of industry experience in computer vision:
- Image segmentation, object detection, and feature extraction on large-scale or high-resolution image data (e.g., whole slide images)
- Designing and developing at least one novel deep learning architecture applied to real-world data
- 2+ years of experience working with cloud infrastructure, data pipelines, and deploying models into production-grade systems
Experience collaborating in team-based codebases, with strong knowledge of version control and Git workflows
Passion for good documentation, code style, and packaging for collaboration
Strong communication skills in English and ability to work cross-functionally
Comfortable working independently in a remote, fast-paced environment
Work permit valid in Switzerland, with a willingness to travel if needed

Strong Plus:

Experience with digital pathology or medical imaging
Background in biology with an understanding of cell morphology
Familiarity with regulatory environments (e.g., FDA, CE marking)
Experience with explainable AI techniques and model interpretability

Company

Moonlight AI AG

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Basel, Switzerland
Berlin, Germany

Contact information

Nicole H. Romano
[email protected]

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Machine learning engineer (computer vision)

PI Data Historian, Integration System Engineer (a) 80 - 100%

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