We are looking for a Senior Machine Learning Engineer to join an innovative AI-driven digital pathology project at the intersection of Machine Learning, Computer Vision, and biomedical imaging.
You will work alongside AI researchers, biomedical experts, and software engineers to develop and deploy advanced Computer Vision solutions for high-resolution tissue imaging, contributing across the full ML lifecycle - from experimentation and model development to scalable production deployment.
Job location: Remote / Serbia
Responsibilities
- Design, develop, and optimize advanced Machine Learning and Computer Vision models for biomedical and digital pathology imaging
- Build scalable ML pipelines for processing and analyzing large-scale, high-resolution imaging datasets
- Develop and train deep learning models using Python and PyTorch
- Conduct experiments, evaluate model performance, and apply techniques such as cross-validation, hyperparameter tuning, and model optimization
- Take models from experimentation to production deployment, ensuring scalability, reliability, performance, and maintainability
- Work with large imaging datasets, including data preprocessing, augmentation, training, validation, and evaluation
- Collaborate closely with AI researchers, biomedical experts, and software engineers to translate complex domain problems into effective ML solutions
- Apply strong software engineering practices to ML development, including version control, testing, code reviews, reproducibility, and documentation
- Continuously evaluate new approaches and advancements in Computer Vision, deep learning, and biomedical imaging and apply relevant techniques to the product
Requirements
- 5+ years of hands-on experience developing Machine Learning solutions, with significant experience in Computer Vision and deep learning
- Degree in Computer Science, Electrical Engineering, Machine Learning, Data Science, or a related technical field
- Strong proficiency in Python
- Strong hands-on experience with PyTorch or comparable deep learning frameworks such as TensorFlow
- Solid understanding of modern Computer Vision architectures, training techniques, model evaluation, and optimization
- Experience working with large-scale image datasets and image-processing pipelines
- Proven experience taking ML models beyond experimentation and deploying them into production environments
- Experience with AWS or another major cloud platform and production ML workloads
- Strong software engineering fundamentals and experience writing clean, maintainable, production-quality code
- Experience with Git-based development, code reviews, testing, and collaborative software development workflows
- Strong analytical and problem-solving skills and the ability to work on complex, research-oriented technical challenges
- Ability to collaborate effectively with multidisciplinary and distributed teams
- Excellent knowledge of English, both written and spoken
Nice to Have
- Experience with biomedical imaging, digital pathology, medical imaging, or healthcare-related ML applications
- Experience working with very large or high-resolution images, such as microscopy or whole-slide imaging
- Familiarity with OpenCV, scikit-learn, Keras, or other relevant ML and image-processing libraries
- Experience with Docker and Kubernetes
- Experience with MLOps practices, model monitoring, experiment tracking, and reproducible ML pipelines
- Experience optimizing deep learning workloads for performance and scalability
- Experience working in research-intensive environments and translating experimental approaches into production-ready solutions