Machine Learning Engineer (m/w/d)

Daisytuner is building the software layer for the next generation of computing. We make complex software run efficiently on any processor from CPUs and GPUs to novel accelerators using a self-learning compiler and cloud-scale optimization infrastructure.
Our team brings together researchers and engineers from RWTH Aachen, TU Munich, TU Darmstadt, and ETH Zurich to tackle some of the hardest problems in systems and infrastructure software. If you want to work on deeply technical challenges with real-world impact, join us and help shape the future of compute.

As a Machine Learning Engineer at Daisytuner, you will work on machine learning challenges at the intersection of software, hardware, and performance. Your work will help us build intelligent systems that understand complex workloads and improve how software runs on modern processors.

What you will be doing:

• Develop and improve deep learning models that support our core optimization and search systems
• Explore modern ML techniques and evaluate their applicability to structured program and performance data
• Design and implement data pipelines for training and evaluation
• Define meaningful features, targets, and metrics for real-world modeling tasks
• Systematically evaluate model variants and validate their practical impact
• Collaborate closely with compiler and infrastructure engineers

What you are bringing:

• Background in Machine Learning, Computer Science, or a related field (degree or equivalent experience)
• Strong Python programming skills and experience building ML systems
• Experience working with structured or non-standard data domains (e.g., graphs, sequences, or systems data)
• Solid understanding of model evaluation methodologies
• Interest in systems topics such as compilers, performance, or hardware (a plus)
• Familiarity with C++ or systems programming is a plus
• Strong communication skills in English (German is a plus)
• A pragmatic, structured working style and willingness to take ownership in an early-stage environment

We are an equal opportunity employer and welcome applications from people of all backgrounds. We value diversity and believe that different perspectives make us stronger. We do not discriminate based on gender, nationality, ethnic origin, religion, disability, age, sexual orientation, or identity.

Job Types: Full-time, Permanent

Work Location: Hybrid remote in Darmstadt