Open-Source Machine Learning Engineer in Switzerland at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for an Open-Source Machine Learning Engineer in Switzerland.

This role offers the opportunity to contribute directly to one of the most influential open-source machine learning ecosystems in the world. You will work on widely used libraries and frameworks that power modern AI development, helping improve tools used by millions of developers, researchers, and data scientists globally. The position is highly collaborative and community-driven, involving close interaction with contributors and users across GitHub and other open forums. You will help shape the evolution of core ML libraries, ensuring they remain efficient, accessible, and cutting-edge. This is an impactful engineering role for someone passionate about open-source innovation, deep learning systems, and building tools that empower the broader AI community. You will operate in a distributed, global environment where transparency, collaboration, and technical excellence are central to daily work.

• Contribute to the development, improvement, and maintenance of major open-source machine learning libraries and frameworks.
• Design and implement high-quality, well-tested, and maintainable Python-based library code used by the global ML community.
• Collaborate with contributors and users through GitHub issues, pull requests, forums, and community discussions.
• Improve deep learning frameworks and tooling, particularly around transformer models, training workflows, and inference optimization.
• Support and enhance ecosystem libraries such as PyTorch-based tooling and related ML infrastructure components.
• Participate in technical discussions to define roadmap priorities and shape the evolution of open-source projects.
• Help debug, review, and improve community contributions while maintaining high code and documentation standards.
• Work on performance improvements, scalability, and usability enhancements for large-scale ML systems.

Requirements:

• Strong proficiency in Python with a focus on writing clean, maintainable, and production-quality library code.
• Solid hands-on experience with deep learning frameworks, particularly PyTorch (JAX or TensorFlow also considered).
• Familiarity with modern machine learning concepts, including transformer architectures and large-scale model training.
• Demonstrated experience contributing to open-source projects with visible contributions on GitHub.
• Experience working with or within the Hugging Face ecosystem or similar ML libraries is a strong advantage.
• Ability to collaborate effectively in open-source environments, including code reviews, issue tracking, and community support.
• Strong understanding of distributed collaboration workflows and asynchronous communication practices.
• Excellent written English skills for technical documentation and global collaboration.
• Bonus: experience with distributed training, GPU optimization, inference performance, or maintaining open-source ML projects.

Benefits:

• Competitive compensation package with equity participation opportunities.
• Fully remote role with flexible working arrangements across Europe, including the United Kingdom.
• Opportunity to work on globally adopted open-source ML tools used by millions of practitioners.
• Strong culture of learning, research collaboration, and continuous technical development.
• Access to conferences, training, and professional development support.
• Flexible working hours and generous time-off policies supporting work-life balance.
• Collaborative, inclusive, and globally distributed engineering culture.
• Opportunity to influence the direction of major machine learning frameworks and tools.
• Work alongside leading contributors in the open-source AI and ML ecosystem.