TransferLab
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About
The TransferLab aims to identify, test and disseminate established and emerging techniques in machine learning in order to provide practitioners and businesses with the best tools for their applications. We constantly survey multiple fields in AI/ML with the goal of distilling useful knowledge for practitioners in industry and academia. Research at the TransferLab is not measured in publications or conference appearances but by its long-term impact on the people and companies applying machine learning. Our work is not done when the paper is published, but when we have created software, trainings, blogposts and other resources that help practitioners to benefit from it. Our areas of interest include Safety and reliability in ML systems, Efficient Machine Learning, Trustworthy and interpretable ML, and Advances and fundamentals in ML.
Platform
Features
• advance fundamentals in ml
• develop trustworthy and interpretable ml
• research efficient machine learning
• focus on safety and reliability in ml systems
• publish blogposts
• offer trainings
• provide software
• identify, test, and disseminate ml techniques
Job Opportunities
AI Research Engineer (m/f/x)
TransferLab is a research initiative that identifies, tests, and disseminates established and emerging machine learning techniques for practitioners and businesses.
Benefits:
Hybrid work model
Budget to visit important conferences, read up on papers and develop skills
Egym wellpass (qualitrain) membership
Regular team events
Public transport subsidy
Education Requirements:
Master's degree in Computer Science, Mathematics, Statistics, Physics, or related technical field
or Bachelor's degree with at least 2 years of experience in professional software engineering
Experience Requirements:
Experience contributing to open-source projects
Experience creating and deploying Machine Learning, Data Science or generative AI Projects
Solid foundation in Python programming and professional software development principles (e.g. unit testing, code reviews, version control)
Expert knowledge in Machine Learning, Statistics and Numerical Methods (Advantageous)
Experience in creating and deploying production ready generative AI solutions, including RAG and Agentic Systems in Python (Advantageous)
Other Requirements:
Team player with curiosity and eagerness to grow in AI/ML engineering, good problem solving skills, and a drive for excellence
Experience in writing on technical topics for a general audience (e.g., blog posts, magazine articles) (Advantageous)
Experience in teaching or creating teaching materials (Advantageous)
Responsibilities:
Contribute to research projects by designing software that allows for quick experimentation and rigorous evaluation of research ideas
Create and deploy GenAI Applications (from RAG to agentic systems) for internal or external use
Support the creation of training materials and demos on GenAI, Machine Learning and Software Engineering
Contribute to open-source Python packages
Participate in hackathons and other events to solve challenges and stay engaged with the AI/ML community
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