• The opportunity to grow. Be at the forefront of building and shaping an industry-defining venture. There are plenty of opportunities to learn and evolve.
• The team to succeed. We are building the leading AI compiler team in Europe. Join our future-focused team to contribute to meaningful, disruptive innovations with us.
• The flexibility you need. We want you to work in the most productive and sustainable way. Whether you need to take extra time off, adjust your schedule, or have other ideas to maximize your productivity, we’ve got your back.
• The compensation that rewards. We are looking for world class talent and pay accordingly. 
• The culture you desire. We actively make space to build our culture. We organize dedicated regular events and retreats for the whole team.

• Design and implement new components of our next generation compiler build upon MLIR
• Explore novel optimization techniques
• Iterate with customers to design the best compiler technology and the best user experience possible
• Partner with a growing open-source community to foster a strong ecosystem around roofline
• The following thesis topics are currently available, please highlight your preferred topic/area in your application: 
  • MLIR Interpreter 
  • Optimizing performance with vector instructions for RISC-V 
  • Blockbuster (new tiling strategy)

• Enrolled student at a European top-level university. (We have relationships to RWTH (Aachen), LMU (Munich) and EPFL (CH), which eases the path to finding a supervisor for students from these unis). 
• Enrolled in a Master's program in Computer Science/ Electrical Engineering or a related field
• Knowledge and hands-on experience in C++ and Python
• Proven understanding of software engineering principles, data structures, design patterns, and algorithms 
• Desire to work with a growing community of open-source contributors
• Ambition and curiosity to solve complex problems, a strong mindset to take ownership of your tasks to drive our solutions forwards, and collaborative attitude to foster our culture

Nice to haves: 

• Experience working with MLIR or LLVM.
• Knowledge of AI algorithms, experience with using AI accelerators or compiling to relevant hardware
• Knowledge of data motion networks, data flow programming models, and optimized AI libraries
• Knowledge about hardware architectures for CPUs, GPUs, or NPUs/accelerators is a plus